Predicting Protein Complexes

Proteins are the workhorses of the cell, and their interactions with one another form the basis of virtually all biological processes. Understanding the composition and dynamics of protein complexes is vital for unravelling the complexities of cellular function, signalling pathways, and disease mechanisms. In recent years, the integration of computational methods and machine learning techniques has revolutionized the prediction of protein complexes, offering new insights into the intricate web of molecular interactions within cells.

Understanding Protein Complexes

Proteins seldom act alone within cells; instead, they often form complexes with other proteins to carry out essential functions. Predicting these protein complexes is fundamental to understanding cellular processes, pathways, and networks.

AI Algorithms for Protein Complex Prediction

AI algorithms, such as deep learning and neural networks, have been employed to analyze protein-protein interaction data and predict potential protein complexes. These algorithms can identify complex patterns within large datasets, enabling the accurate prediction of protein interactions and complex formation.

Advantages of AI in Protein Complex Prediction

• Accuracy: AI algorithms can analyze complex and high-dimensional data to identify intricate relationships, leading to more accurate predictions.
• Efficiency: By automating the analysis process, AI significantly reduces the time and resources required for protein complex prediction.
• Scalability: AI-driven approaches can handle large-scale protein interaction data, allowing for comprehensive analyses of complex biological systems.

Computational Approaches to Protein Complex Prediction

• Network-Based Methods

Network-based approaches analyze protein-protein interaction networks to identify densely connected subnetworks, which are indicative of potential protein complexes. These methods leverage graph theory and algorithms to uncover cohesive modules within interaction networks.

• Structural Bioinformatics

By integrating structural data, computational methods can predict protein complexes based on the complementarity of protein surfaces, binding affinities, and structural constraints, providing valuable insights into the architecture of protein interaction interfaces.

• Machine Learning and Data Mining

Machine learning algorithms, such as support vector machines, neural networks, and clustering techniques, can be trained on diverse biological data to recognize patterns and features associated with known protein complexes, enabling the prediction of novel complexes with high accuracy.

Virus Prevention

Viral diseases have posed significant threats to public health throughout history, often causing widespread illness, economic disruption, and loss of life. While the battle against viruses has been ongoing, the convergence of scientific advancements and technological innovations has provided new avenues for proactive virus prevention. From early detection and surveillance to vaccine development and public health interventions, a multi-faceted approach leveraging the latest scientific knowledge and cutting-edge technologies is crucial in the ongoing effort to prevent the spread of viral infections.

Importance of Virus Prevention

In the context of healthcare and public health, preventing the spread of viruses is of paramount importance. Early detection and proactive measures can mitigate the impact of viral outbreaks and pandemics.

AI for Virus Detection and Prevention

Early Detection

AI-based algorithms can analyze diverse data sources, including genomic sequences, clinical data, and environmental factors, to detect patterns indicative of potential viral outbreaks. This early detection capability is crucial for implementing timely preventive measures.

Vaccine Development

AI plays a pivotal role in expediting vaccine development by predicting potential antigenic targets, optimizing vaccine design, and accelerating the identification of candidate compounds for antiviral drugs.

Utilizing AI for Virus Prevention

• Surveillance: AI algorithms can continuously monitor and analyze various data streams to identify potential signs of viral activity, enabling proactive surveillance and timely interventions.
• Precision Medicine: AI facilitates the development of personalized antiviral strategies by analyzing individual genetic variations and immune responses, leading to more effective prevention and treatment measures.

Future Implications

The integration of AI into protein complex prediction and virus prevention holds immense promise for advancing healthcare and combating infectious diseases. As AI technologies continue to evolve, the ability to accurately predict protein interactions and proactively prevent viral outbreaks will have far-reaching implications for disease management, drug development, and public health strategies.

In conclusion, the utilization of AI for predicting protein complexes and virus prevention represents a significant milestone in the fields of bioinformatics and healthcare. By harnessing the power of AI-driven analytics, researchers and healthcare professionals can gain deeper insights into complex biological processes, leading to more effective strategies for disease prevention and management.

As AI technologies continue to advance, the potential for transformative breakthroughs in protein complex prediction and virus prevention becomes increasingly tangible, offering new hope for addressing some of the most pressing challenges in healthcare and infectious disease control.

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Revolutionizing Healthcare: The Power of Freed AI: https://www.youtube.com/watch?v=-I2vbASTv6k

1. Recursion

Recursion, a pioneering healthcare app, uses artificial intelligence (AI) and machine learning (ML) to evaluate massive volumes of biological data. Recursion intends to discover novel treatments for a variety of diseases, ranging from uncommon genetic abnormalities to complex neurological ailments, by integrating computational biology and powerful algorithms.

Website: https://www.recursion.com/

2. Zebra

Zebra is changing medical imaging by leveraging AI to help radiologists spot irregularities and diagnose diseases more precisely and efficiently. Zebra’s deep learning algorithms enable early diagnosis of ailments such as cancer, cardiovascular disease, and neurological problems, resulting in better patient outcomes and lower healthcare expenditures.

Website: https://www.zebra.com/ap/en.html

3. ProteinQure

ProteinQure is a healthcare software that combines molecular design and artificial intelligence to discover innovative treatments using computational protein design. ProteinQure accelerates drug discovery by simulating protein folding and interactions, resulting in personalised treatments for cancer, infectious illnesses, and autoimmune disorders.

Website: https://proteinqure.com/

4. Viz.ai

Viz.ai, which aims to transform medical imaging interpretation, uses AI-powered algorithms to automate radiological image processing. By supporting radiologists in detecting abnormalities and prioritising crucial cases, iz.ai improves diagnostic accuracy and optimises workflow, resulting in faster treatment decisions and better patient outcomes.

Website: https://www.viz.ai/

5. Eko

Eko uses AI and digital stethoscopes to improve heart monitoring and diagnosis. By studying heart sounds and rhythms in real time, Eko’s app helps healthcare providers spot cardiac issues early, allowing for timely intervention and individualised treatment options.

Website: https://www.ekohealth.com/

6. Healthy.io

Healthy.io, leveraging the widespread availability of cellphones, provides novel solutions for remote urinalysis and chronic kidney disease management. Healthy.io’s smartphone-based urine analysis kits and AI-powered algorithms enable patients to effortlessly monitor their kidney health from home, allowing for early identification of kidney illness and quick medical intervention.

Website: https://healthy.io/

7. Cyclica

Cyclica uses computational biophysics and artificial intelligence to speed up drug research and development by predicting drug-protein interactions and analyzing drug safety and efficacy. Cyclica streamlines drug development by optimizing drug candidate properties and identifying potential off-target effects, while also reducing the chance of adverse responses in patients.

Website: https://cyclicarx.com/

8. Owkin

Owkin’s collaborative intelligence platform connects healthcare institutions, researchers, and AI professionals to speed medical research and medication discovery. Owkin’s federated learning approaches enable secure and privacy-preserving data analysis across decentralized datasets, encouraging cooperation and knowledge sharing while protecting patient privacy.

Website: https://www.owkin.com/

9. Paige

Paige specializes in pathology and uses AI to help pathologists diagnose cancer and other diseases more correctly and effectively. Paige’s software improves diagnostic accuracy, speeds up workflows, and allows for individualized treatment recommendations by evaluating histopathology pictures and recognizing subtle disease-related patterns.

Website: https://paige.ai/

10. Atomwise

Atomwise uses AI-driven virtual screening to speed up drug discovery and repurposing efforts. Atomwise speeds the discovery of new therapies for cancer, infectious illnesses, and neurological disorders by simulating molecular interactions and forecasting prospective medication candidates.

Website: https://www.atomwise.com/

11. Butterfly Network

Butterfly Network’s handheld ultrasound devices, along with AI-powered imaging software, transform medical imaging by making ultrasound more accessible and portable. Butterfly Network’s pocket-sized ultrasound probes and intuitive smartphone interface enable healthcare providers to conveniently do point-of-care ultrasound examinations, allowing for rapid diagnostic and treatment options.

Website: https://www.butterflynetwork.com/

12. Subtle Medical

Subtle Medical improves medical imaging operations by lowering scan durations and radiation doses while retaining image quality using AI-powered post-processing techniques. Subtle Medical enhances picture reconstruction and optimizes imaging protocols to increase patient comfort, throughput, and diagnostic accuracy in a variety of imaging modalities.

Website: https://subtlemedical.com/

13. Concerto HealthAI

Concerto HealthAI uses real-world data and AI-powered analytics to enhance oncology research and improve patient outcomes. Concerto HealthAI offers precision oncology techniques, personalised treatment strategies, and evidence-based decision-making in cancer care by analyzing large datasets containing patient demographics, treatment regimens, and clinical outcomes.

Website: https://www.concertai.com/

These revolutionary healthcare apps are only a small sample of the transformative technology transforming the healthcare environment. These apps have the potential to increase diagnosis accuracy, improve treatment outcomes, and empower patients, promising a brighter, healthier future for people all across the world. As we continue to embrace the digital revolution in healthcare, it is critical that we foster collaboration among technology developers, healthcare providers, policymakers, and patients in order to fully realize the potential of these groundbreaking innovations and ensure equitable access to high-quality healthcare for all.

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Apple Vision Pro used for SPINAL SURGERY:

The introduction of the mixed-reality headset into the operating room marks a new era in surgical help and precision. Hospital owner Bupa told Business Insider that the team, lead by doctors Fady Sedra and Syed Aftab, used the Vision Pro headset’s immersive features to improve their surgical skills. Interestingly, the headset was worn by a scrub nurse rather than a surgeon, demonstrating the collaborative and interdisciplinary character of current medical interventions. The Daily Mail went on to explain how the nurse easily integrated technology into the surgical process, improving the efficiency and efficacy of the surgeries.

This innovative technology owes much to eXeX, a provider of healthcare-specific technology platforms. Aftab, a consultant orthopaedic spinal surgeon, underlined the importance of the Apple Vision Pro in transforming patient care as part of their relationship. He stated, “Working with eXeX to use the Apple Vision Pro has made a significant difference in the way we provide care to our patients.” The program is seamless and has increased efficiency within the Complex Spine team,” emphasising the practical benefits of this integration.

This pioneering development is consistent with a larger trend in the healthcare sector, which is marked by the convergence of technology and medicine. Apple’s Vision Pro device was just launched in the United States, and a variety of healthcare applications compatible with the headset have surfaced, according to an Apple press release. Stryker’s Mako SmartRobotics stands out among these, with an app designed specifically for surgeons who specialise in hip and knee replacements, shortening surgical processes and improving patient results.

Furthermore, the advent of companies such as Fundamental Surgery demonstrates the transformational potential of virtual reality in surgical training. By providing immersive, hands-on experiences, these platforms allow prospective surgeons to perfect their skills in a secure and regulated setting. Similarly, Cedars-Sinai’s mental health support through meditation and deep breathing exercises exemplifies modern healthcare’s holistic approach, which acknowledges the connection of physical and mental health.

Susan Prescott, Apple’s VP of Worldwide Developer Relations, expressed appreciation for the numerous applications created by the healthcare community for the Apple Vision Pro. In a press release, she stated, “We’re thrilled to see the incredible apps that developers across the healthcare community are bringing to Apple Vision Pro,” emphasising Apple’s commitment to encouraging innovation and collaboration in the field.

Furthermore, Meta’s entrance into virtual reality has sparked tremendous interest, notably in the field of surgical simulation. CNBC reported on how doctors at Kettering Health Dayton in Ohio use Meta’s virtual reality headgear, the Quest 2, to practise surgery using 3D simulations. This novel approach allows surgeons to become acquainted with complex operations and anatomical details, similar to how a pilot uses a flight simulator before ascending to the sky.

Finally, the use of Apple’s Vision Pro headset during surgical procedures at Cromwell Hospital symbolises a paradigm leap in healthcare delivery. By leveraging mixed reality technology, surgeons may now traverse complex procedures with unparalleled precision and confidence, resulting in better patient care and results. As the healthcare sector evolves, powered by technological innovation and creative collaborations, one thing is certain: the future of medicine is becoming increasingly entwined with the limitless possibilities provided by modern technology.

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Premier Radiology Services has long prioritized patient care and empowered radiologists with the best tools available to improve outcomes. With its recent acquisition of National Rad and increased patient volume, the practice recognized the need for innovative solutions to expedite patient triage and enhance diagnostic efficiency.

Drew Gaudet, CEO of Premier Radiology Services, commented on the significance of this partnership, stating, “Navigating the landscape of AI solutions independently was challenging. Our re-evaluation of AI initiatives led us to conclude that collaborating with Ferrum Health to consolidate our infrastructure and gain access to clinical analytics would support our growth initiatives and, most importantly, improve patient care.”

Premier Radiology Services will deploy Gleamer’s BoneView integrated into the Ferrum AI platform. This enables the practice to prioritize thousands of patients daily, swiftly directing routine cases to appropriate care pathways.

Gaudet added, “Ferrum’s rigorous vetting process ensures that best-in-class AI tools are integrated into the platform and can be easily and safely deployed.”

Pelu Tran, CEO of Ferrum Health, emphasized the importance of data security and AI validation in healthcare AI deployments, stating, “Data security and automated AI validation and monitoring are paramount in every healthcare AI deployment. Our partnership with Premier Radiology Services exemplifies our shared commitment to upholding the highest patient care and data integrity standards.”

Based in Miami, Florida, Premier Radiology Services, LLC is a leading provider of teleradiology services, offering 24/7 coverage across a range of modalities and sub-specialties. With a network of over 120 radiologists, Premier interprets more than two million radiology exams annually for a wide range of customers, serving the needs of primary care providers, mobile imaging providers, occupational health centers, urgent care providers, and outpatient imaging centers.

About Ferrum Health: Ferrum Health is an enterprise-scale AI platform designed as the reference architecture for AI deployments for health systems and radiology practices. With a focus on private deployment (data security), autonomous AI validation, and business intelligence, Ferrum Health provides the infrastructure to deploy the best-in-class AI applications at enterprise scale.

For media inquiries, please contact:
Ferrum Health
George Gilligan
Enterprise Brand Manager
george@ferrumhealth.com

SOURCE Ferrum Health Inc.

https://www.prnewswire.com/news-releases/ferrum-health-premier-radiology-services-partner-to-enhance-patient-care-and-operational-efficiency-302085608.html

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SAN FRANCISCO and BOSTON, March 12, 2024 /PRNewswire/ — Alife Health (“Alife”), a leading fertility technology company specializing in the development of AI tools for in vitro fertilization (IVF), has announced a groundbreaking partnership with Boston IVF, a leading fertility clinic with more than 25 locations across the U.S., to pilot the country’s first AI tool for IVF medication optimization. Boston IVF will implement Alife’s Stim Assist software, which is designed to help IVF clinicians retrieve the optimal number of eggs for each patient and reduce overall medication costs.

“Our partnership with Alife marks a major milestone in the advancement of AI technology for fertility treatment.”Post this

The collaboration aims to advance the field of reproductive medicine by combining Alife’s state-of-the-art AI technology with the expertise of Boston IVF’s world-renowned fertility specialists. By leveraging advanced machine learning algorithms, they hope to enhance the accuracy of IVF treatment protocols, ultimately improving the success rates for couples trying to conceive through assisted reproductive technologies.

“Our partnership with Alife marks a major milestone in the advancement of AI technology for fertility treatment,” says David Stern, CEO of Boston IVF. “At Boston IVF, we are always looking for new cutting-edge technologies to research, test, and integrate into our practices to provide the best possible care for our patients. By exploring the potential that AI technology can bring to our field, we aim to establish a new standard for IVF and continue to bring hope to millions of couples struggling with infertility.”

Alife’s Stim Assist software draws on data from tens of thousands of historical IVF patient cycles to generate data-driven insights. These insights can help clinicians understand what treatment has produced the best outcomes for similar patients, giving them the power to design a personalized treatment protocol, backed by data. The partnership will allow Boston IVF’s team of experienced fertility specialists to integrate Alife’s AI software into their practice, providing their patients with innovative and effective solutions.

“Boston IVF, with its extensive network of fertility clinics and a long-standing reputation for excellence in reproductive medicine, was a natural choice for this collaboration,” says Paxton Maeder-York, CEO and founder of Alife. “Our past research has shown that using our Stim Assist software has produced improvements in both patient egg yield and cost savings. We couldn’t be more excited to partner with this storied institution as we pilot this software to demonstrate the immense promise that AI presents for the IVF industry.”

About Alife Health
Alife’s mission is to personalize and modernize the IVF process with cutting-edge artificial intelligence technology to improve outcomes and care for all. The company has built a consortium of partnerships with the top clinics and most renowned physicians to bring significant clinical improvements to patients globally. Founded by Paxton Maeder-York in 2020, the company is based in San Francisco and backed by top-tier venture capital investors including Lux Capital, Union Square Ventures and Maveron. To learn more visit www.alifehealth.com.

About Boston IVF
Boston IVF is one of the largest and most experienced fertility networks in the United States, with more than 150,000 babies born since 1986. Founded as one of the nation’s first private practice IVF centers, the Boston IVF network has grown to include 40 reproductive endocrinologists across nearly 30 centers throughout Massachusetts, Maine, New Hampshire, Rhode Island, New York, Delaware, Idaho, Indiana, North Carolina, Ohio, and Utah.

A renowned innovator of reproductive technologies, advanced protocols, and cutting-edge research, Boston IVF has achieved numerous “firsts” in reproductive care. Its scientific and research arm continues to pave the way for breakthroughs in fertility care and its accredited REI Fellowship Program has graduated numerous reproductive endocrinologists as part of its mission to train the next generation of fertility experts. In 2024, Boston IVF joined the global IVI RMA Network, contributing to the network’s management of more than 20+ labs and 60 satellites across North America.

Contact Info
Alife Health: Jamie Gray, press@alifehealth.com, 310-699-3163
Boston IVF: Emily Redfern, eredfern@bostonivf.com, 617-217-1038

SOURCE Alife Health

https://www.prnewswire.com/news-releases/alife-health-partners-with-boston-ivf-on-ai-technology-for-ivf-treatment-optimization-302086032.html

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SILVER SPRING, Md., March 12, 2024 /PRNewswire/ — Capital Digestive Care, the largest private gastroenterology (GI) practice in the Mid-Atlantic region, today announced that it is launching LGI-Flag in the United States. Available through the Roche navify Algorithm Suite, LGI-Flag is a groundbreaking AI-driven algorithm used to flag individuals at risk for lower GI disorders that warrant further evaluation. With this launch, the Capital Digestive Care Laboratory – the first GI specialty practice recognized as a Roche Diagnostics Center of Excellence – will now use LGI-Flag to screen eligible patients using electronic health record (EHR) and clinical data repositories, contact those identified as being at risk for colorectal cancer and/or other lower GI disorders, and schedule appropriate follow up (e.g., a colonoscopy).

“Capital Digestive Care is committed to enabling the digital transformation of healthcare, in order to provide a more personalized, convenient and predictive continuum-of-care for patients,” said Michael Weinstein, M.D., CEO of Capital Digestive Care. “Our innovative laboratory, along with our end-to-end continuum-of-care model, makes us an ideal organization to bring this highly sensitive and well-validated tool to provide more precise and predictive care to patients. Now, we have a means to more precisely identify those at high risk of lower GI disorders, including colorectal cancer so they may avoid the devastating effects of the disease through increased screening and earlier detection and treatment.”

LGI-Flag uses demographic information and historical CBC (complete blood count) test results to flag individuals with CBC patterns that may be associated with an increased risk for lower GI disorders, including but not limited to irritable bowel syndrome (IBS), inflammatory bowel diseases (IBD), and colorectal cancer – the third leading cause of cancer-related deaths in both men and women in the United States.¹

Increasing colorectal cancer screening rates has been a priority in the United States for some time, as outcomes improve significantly when asymptomatic polyps and other early-stage cancers are detected and treated early. The U.S. Preventive Services Task Force (USPSTF) colorectal screening guidelines recommend a colonoscopy every 10 years for adults between the ages of 45 and 75 who are considered to be at low to average risk. In addition, the guidelines recommend a non-invasive stool-based screening test, such as the guaiac-based fecal occult blood test (HSgFOBT) or fecal immunochemical test (FIT) (which are recommended annually) and Stool DNA-FIT (which is recommended every 1-3 years).² However, approximately 32% of age-eligible U.S. adults do not follow the current colorectal cancer screening guidelines³ and only approximately 37% of cases are diagnosed at an early stage.⁴

LGI-Flag can be used on its own to identify patients at increased risk, or with a non-invasive stool-based screening test to provide additional information about an individual’s risk and whether they require further evaluation versus a stool-based screening test alone.

“We’re excited that through Capital Digestive Care, LGI-Flag will now be offered to a large number of patients in the U.S. to help improve care for people with wide-ranging lower GI disorders and support the critical mission to increase colorectal cancer screening rates,” said Moritz Hartmann, Global Head of Roche Information Solutions. “This helps advance that mission by offering a highly effective and clinically validated machine-learning-based algorithm to identify those at increased risk of a wide array of lower GI disorders, including colorectal cancer.”

About LGI-Flag

LGI-Flag, developed by Medial EarlySign and available via the navify Algorithm Suite from Roche, is an evidence-based way to identify patients who are at risk for colorectal cancer and other lower GI disorders. The tool requires only a patient’s existing CBC results, along with the individual’s birth year and gender, to calculate a risk score and flag those in need of follow-up screening.

A prospective real-world study published in the New England Journal of Medicine in 2022 identified patients overdue for colorectal cancer screening and used LGI-Flag to flag those at highest risk for abnormal results.⁵ Patients were then informed of their risk and offered to schedule a colonoscopy to complete their screening. Of those flagged patients, approximately 70% had a significant finding. Overall, colorectal cancer was found in 8% of flagged patients who underwent a colonoscopy and had their results documented, 22% were found to have advanced adenomas (a classification of colon polyps that have a higher likelihood of developing into malignant polyps), and 29% were found to have adenomas/polyps.

“We’re proud to now offer LGI-Flag to our large and diverse body of patients to help improve health outcomes without increasing patient burden,” said Laura Vivian, Executive Director of Capital Digestive Care Laboratory. “This launch builds upon our existing relationship with Roche Diagnostics and will further advance our ability to seamlessly deliver more personalized and actionable insights to revolutionize care for the patients we serve.”

About Capital Digestive Care

Founded in 2009, Capital Digestive Care is the largest private gastroenterology practice in the Mid-Atlantic. Recent partnerships with Gastrointestinal & Liver Specialists of Tidewater and Gastroenterology, Ltd. in Southeastern Virginia have expanded its network to more than 160 physicians and advanced care practitioners who treat a wide range of conditions—from the common complaint of heartburn to the complex management of Crohn’s Disease—and offer critical services for the prevention of colon cancer for more than 200,000 patients annually.

With business operations located in Silver Spring, MD, Capital Digestive Care’s integrated care model connects its doctors to more than 25 office locations and outpatient surgery centers as well as specialized laboratory services and the largest clinical research program of its kind in the region. For more information, please visit www.capitaldigestivecare.com.

Contact:

Heather Shea
+1 617-286-2013
heather.shea@catalyticagency.com

SOURCE Capital Digestive Care

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NEW YORK, March 12, 2024 /PRNewswire/ — Hyro, a leading provider of Responsible AI-Powered Communications for healthcare, and Disruptive Innovations, a renowned digital business and technology consulting firm specializing in healthcare, today officially announced their existing, long-term strategic partnership.

Disruptive Innovations, known for its expertise in crafting customized solution blueprints for forward-thinking health systems, identified Hyro as an ideal partner due to its industry-leading voice AI technology. Integrating Hyro’s Responsible AI platform will enable Disruptive Innovations’ clients to safely and securely address key challenges, including:

• Reducing agent burnout: Hyro’s voice AI assistants handle routine patient inquiries, freeing up valuable agent time for complex cases and personalized interactions, leading to improved job satisfaction and reduced turnover.
  
• Improving patient access: 24/7 availability of voice AI assistants ensure patients receive timely answers and can manage appointments and prescription refills conveniently without enduring long hold times.
  
• Enhancing patient experience: Natural language understanding (NLU) and personalized responses offered by Hyro’s AI assistants create more engaging experiences, minimizing friction and improving overall satisfaction.
  
• Enhancing operational efficiency: Hyro’s platform generates actionable ROI-driving insights that optimize workflows and streamline processes, enabling data-driven decision-making.
  
• Reducing time to value: Hyro’s AI assistants eliminate the need to build complex in-house solutions with the fastest deployment time in the industry and an average of 5.5x ROI within 6 months of implementation. 

“Disruptive Innovations is thrilled to formally announce our strategic partnership with Hyro, a leading Responsible AI-Powered Communications platform in the healthcare space,” said David Wright, Founder & CEO of Disruptive Innovations. “Having worked closely with Hyro for some time, we have been continually impressed not only by the solution they offer but by the people that make up the organization and their dedication to the clients they provide for. Aligning ourselves with a partner such as Hyro brings us one step closer in our journey to offer a radically convenient patient experience for all those seeking care and to empower the healthcare providers that serve them.”

This press release was issued through 24-7PressRelease.com. For further information, visit http://www.24-7pressrelease.com.

SOURCE Hyro

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• Diagnosing Patients: AI algorithms analyze medical imaging data, such as X-rays, MRIs, and CT scans, to assist healthcare professionals in accurate and swift diagnoses.
• Transcribing Medical Documents: Automatic Speech Recognition (ASR) technology employs advanced algorithms and machine learning models to convert spoken language into written text, providing a more efficient and accurate method for documenting medical information.
• Drug Discovery and Development: AI accelerates the drug discovery process by analyzing vast datasets to identify potential drug candidates and predict their efficacy.
• Administrative Efficiency: AI streamlines administrative tasks, such as billing and scheduling, reducing paperwork and improving overall operational efficiency within healthcare organizations.
• Precision medicine: AI is used to produce personalized treatment plans for patients that take into account such factors as their medical history, environmental factors, lifestyles, and genetic makeup. 

AI already plays an important role in healthcare, and it has a very bright future as capabilities continue to advance and grow. It is positioned to improve patient outcomes, increase safety, reduce human error, and reduce costs associated with healthcare, along with many other things.

T

Image credit: https://hbr.org/2018/05/10-promising-ai-applications-in-health-care

Top 10 AI applications in healthcare industry

1. IBM Watson Health

It is a prominent application of artificial intelligence in healthcare. It combines AI, machine learning, and natural language processing to analyze vast amounts of medical data and assist healthcare professionals in making more informed decisions.  It uses AI to assist doctors in identifying personalized, evidence-based treatment options by analyzing vast amounts of medical literature, clinical trial data, and patient records. By harnessing the power of AI and cognitive computing, IBM Watson Health aims to transform healthcare delivery, empower healthcare professionals with data-driven insights, and ultimately improve patient outcomes.

2. Google DeepMind Health

This AI app is a division of DeepMind, an artificial intelligence research lab owned by Google. DeepMind Health focuses on developing AI-powered solutions to address complex healthcare challenges and improve patient care.  It focuses on predicting protein folding, which is crucial for understanding diseases and developing new drugs. This technology can help in drug discovery and protein structure prediction.

 Some applications of Google DeepMind Health are:

1. Medical Image Analysis: DeepMind Health has worked on AI models to analyze medical images, such as retinal scans, to detect and diagnose conditions like diabetic retinopathy and age-related macular degeneration.
2. Patient Monitoring and Predictive Analytics: DeepMind Health has developed AI systems to analyze patient data and predict deterioration. 

3. Zebra Medical Vision

Zebra Medical Vision is a leading company that uses artificial intelligence and machine learning to develop advanced medical imaging analytics. Their AI-powered platform aims to assist radiologists and healthcare professionals in detecting and diagnosing various medical conditions. 

Some key applications of Zebra Medical Vision include:

1. Quantitative Imaging Biomarkers: Zebra Medical Vision’s platform can automatically extract quantitative measurements and biomarkers from medical images. This allows for objective and standardized assessments of conditions like osteoporosis, fatty liver, and coronary artery calcifications.
2. Triage and Prioritization: Zebra Medical Vision’s algorithms can assist in triaging and prioritizing medical cases based on the severity of detected abnormalities. 
3. Longitudinal Tracking: Zebra Medical Vision’s platform enables the tracking and comparison of medical images over time. This is particularly useful for monitoring disease progression, evaluating treatment response, and identifying potential changes in a patient’s condition.

4. Butterfly Network

Butterfly Network is a company that specializes in developing handheld, pocket-sized ultrasound devices powered by artificial intelligence. Their innovative technology combines hardware and software to provide accessible and high-quality medical imaging solutions. 

The Butterfly iQ, their flagship product, is an ultrasound device that connects to a mobile device or tablet. It incorporates advanced AI algorithms and machine learning to deliver real-time imaging capabilities for a wide range of medical applications. Butterfly Network’s technology allows healthcare providers to store, access, and share ultrasound images securely through their cloud-based platform. This facilitates collaboration, remote consultations, and longitudinal tracking of patient imaging data. The combination of portability, AI-powered imaging, and cloud connectivity positions Butterfly Network’s technology as a promising solution for point-of-care ultrasound. It empowers healthcare professionals with advanced imaging capabilities and has the potential to improve patient outcomes, particularly in resource-limited or remote settings.

5. Aidoc

Aidoc is a leading provider of AI-powered radiology solutions that aim to enhance the accuracy and efficiency of radiology diagnoses. This platform uses deep learning algorithms to analyze medical images and assist radiologists in detecting and prioritizing critical findings.

1. Advanced Imaging Analytics: Aidoc’s AI algorithms analyze medical images, such as CT scans, MRIs, and X-rays, to identify and flag abnormalities and critical findings. 
2. Workflow Prioritization: Aidoc’s platform integrates seamlessly into radiology workflows, providing a triage system that automatically prioritizes cases based on the urgency of detected abnormalities. This helps radiologists manage their workload efficiently and ensures that critical cases receive prompt attention.
3. Quality Improvement: Aidoc’s algorithms not only aid in identifying abnormalities but also provide quality improvement insights by detecting common imaging errors or discrepancies. 

6. Tempus

Tempus is a technology company that utilizes artificial intelligence and data analytics to drive advancements in precision medicine. The company’s mission is to empower healthcare professionals with data-driven insights and tools to deliver personalized care and improve patient outcomes. Tempus focuses on building an extensive library of clinical and molecular data, along with advanced analytics capabilities, to enable precision medicine in various areas. Tempus aims to bridge the gap between technology and healthcare, leveraging AI and data analytics to unlock the potential of precision medicine. By combining molecular and clinical data, they strive to enable more personalized and targeted therapies, ultimately improving patient outcomes.

7. Path AI

Path AI is a company that specializes in applying artificial intelligence and machine learning to pathology. Their goal is to improve accuracy and efficiency in diagnosing diseases through advanced image analysis and data-driven insights.

The main applications of  Path AI’s technology are:

1. Digital Pathology: Path AI digitizes and analyzes pathology slides using high-resolution scanning technologies. This allows for the creation of a digital pathology repository that can be accessed and analyzed using AI algorithms.
2. Disease Diagnosis and Classification: Path AI’s algorithms assist pathologists in accurately diagnosing and classifying diseases, such as cancer. By analyzing digital pathology images, the algorithms can detect patterns, identify biomarkers, and provide quantitative measurements, helping pathologists make more informed diagnoses.
3. Prognostic and Predictive Analytics: Path AI’s technology can analyze digital pathology images and patient data to provide prognostic insights. 
4. Drug Development and Research: PathAI collaborates with pharmaceutical companies and researchers to accelerate drug development and clinical trials. 

Path AI aims to enhance pathology practices by integrating AI and machine learning into the interpretation of digital pathology images. 

8. Gauss Surgical

Gauss Surgical is a healthcare technology company that specializes in developing AI-driven solutions for surgical and perioperative care. Their focus lies in leveraging data analytics and artificial intelligence to enhance patient safety, improve surgical outcomes, and optimize the surgical workflow.

Key aspects and applications of Gauss Surgical’s technology include:

1. Blood Loss Monitoring: Gauss Surgical’s AI algorithms analyze real-time video footage from surgical procedures to accurately estimate and monitor blood loss. This helps healthcare providers proactively manage bleeding during surgery and make informed decisions regarding transfusions and interventions.
2. Real-time Decision Support: Gauss Surgical’s platform offers real-time feedback and decision support to surgeons and anesthesiologists during surgical procedures. This assists in optimizing surgical techniques, managing blood loss, and improving patient safety in the operating room.

Gauss Surgical’s AI-driven solutions aim to enhance surgical care by providing objective, data-driven insights and decision support. 

9. OWKIN

OWKIN is a company that harnesses the power of artificial intelligence and machine learning to transform medical research and improve healthcare outcomes. They specialize in building collaborative platforms and advanced analytics tools that enable data sharing and analysis while ensuring privacy and security. OWKIN’s innovative approach to collaborative and privacy-preserving AI in healthcare research has the potential to revolutionize medical discoveries and drive advancements in precision medicine

Key aspects and applications of OWKIN’s technology include:

1. Federated Learning: OWKIN’s platform enables collaboration among healthcare institutions and researchers by utilizing federated learning. This approach allows the sharing and analysis of data while keeping it decentralized and secure, maintaining data privacy and compliance with regulations.
2. AI Models for Medical Research: OWKIN develops AI models that can analyze diverse datasets, including clinical data, imaging data, and genomics data. These models assist researchers in extracting meaningful insights, identifying patterns, and discovering new correlations to advance medical research.

10. Prognos

Prognos is a healthcare analytics company that leverages artificial intelligence and advanced analytics to transform patient data into actionable insights. They specialize in applying data-driven approaches to improve disease identification, treatment decisions, and patient outcomes.

Key aspects of Prognos’ technology include:

1. Predictive Analytics: Prognos’ AI algorithms analyze large volumes of patient data, including lab results, claims data, and EHR data, to identify patterns and predict disease outcomes. This helps healthcare providers intervene earlier, personalize treatment plans, and improve patient management.
2. Disease Registry and Stratification: Prognos’ platform enables the creation of disease registries by aggregating and analyzing patient data. This helps identify high-risk populations, stratify patients based on disease severity, and facilitate targeted interventions and preventive measures.
3. Real-world Evidence Generation: Prognos analyzes real-world data to generate evidence on treatment outcomes, disease progression, and the effectiveness of interventions. This real-world evidence can support clinical research, inform clinical guidelines, and facilitate evidence-based decision-making.

By harnessing the power of AI and analytics, Prognos aims to unlock the value of healthcare data and empower healthcare organizations with actionable insights.

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• Pain Distraction and Management

Virtual reality has demonstrated enormous promise in diverting patients from severe discomfort during medical operations. Healthcare professionals can minimize the need for traditional pain management procedures by effectively reducing patients’ perception of pain through the use of virtual environments.

• Surgical Training and Simulation

Surgeons can receive training on a safe and affordable platform with VR-based surgical simulators. Surgeons can perform difficult procedures in an immersive environment, hone their abilities, and become acquainted with novel surgical techniques owing to these simulators.

• Phobia Treatment

Virtual reality has shown promise as a treatment for anxiety disorders and phobias. Therapists can help patients overcome their concerns by gradually acclimating them to virtual circumstances that trigger their phobias in a safe atmosphere.

• Physical Rehabilitation

VR technology is being applied to improve programs for physical rehabilitation. Patients can participate in engaging and stimulating activities that facilitate their recuperation from surgeries or accidents by use of interactive virtual reality workouts.

• Medical Education

VR is transforming medical education by offering immersive learning experiences for students and professionals. From exploring 3D anatomical models to interactive medical case simulations, VR is revolutionizing the way medical knowledge is imparted and retained.

• Stress Reduction

Healthcare settings can be stressful for both patients and medical staff. VR technology provides a tool for relaxation and stress reduction through immersive relaxation experiences and mindfulness exercises.

• Telemedicine and Remote Consultations

By building realistic virtual worlds that allow patients and healthcare providers to interact and communicate in real-time, virtual reality (VR) is enabling telehealth and remote consultations by removing the boundaries of physical distance.

Conclusion

The mentioned uses of VR in healthcare only scratch the surface of its enormous promise. VR technology has the potential to revolutionize therapy, medical education, and patient care as it develops. Healthcare practitioners may transform the way healthcare is provided, improve patient outcomes, and raise the standard of care by adopting these immersive innovations.

We must keep up with these advancements as thought leaders in the B2B market and look for ways to incorporate VR technologies into healthcare goods and services. Through the utilization of immersive innovations, business-to-business (B2B) organizations can significantly influence the direction of healthcare delivery and promote patient-centred care.

The post The VR Healthcare Revolution: Exploring the Next Wave of Immersive Innovations first appeared on AITechTrend.

In light of its benefits, including low error rate, 24/7 availability, real-time insight generation, and quick analysis, Artificial Intelligence (AI) is becoming more and more integrated into our daily lives. AI is finding useful applications in clinical medical and dental healthcare analytics, such as disease diagnosis, risk assessment, treatment planning, and drug discovery. Its use in these domains is growing.

AI’s application in healthcare has the potential to completely transform patient care, diagnosis, and therapy. This essay attempts to examine the potential applications of AI in medicine as well as give a quick overview of its past.

The Early Beginnings or Outlining its Past

When scientists started looking at the possibilities of AI methods in clinical decision-making in the 1960s, medicine as we know it today was born.

One of the earliest uses was in diagnostic and therapy suggestion using rule-based expert systems.

AI Applications in Healthcare

AI has made significant strides in revolutionizing various aspects of the healthcare industry, with applications across diagnostics, medical imaging, pharmaceuticals, hospital information systems, medical research, emergency room and surgery, as well as the treatment of mental health.

• AI in Diagnostics

AI has greatly improved diagnostic processes by analysing complex medical data to identify patterns and predict potential health issues. Through machine learning algorithms, AI can assist healthcare professionals in making accurate and timely diagnoses based on a wide array of patient data.

• AI in Medical Imaging

AI’s integration into medical imaging has enhanced the interpretation of medical scans such as X-rays, MRIs, and CT scans. By leveraging deep learning algorithms, AI can aid in the early detection of diseases, potentially leading to earlier intervention and improved patient outcomes.

• AI in Pharmaceuticals & New Drug Development

In pharmaceuticals, AI is streamlining the drug discovery and development process. By analyzing extensive biological and chemical data, AI can identify potential drug candidates, predict their efficacy, and even design novel compounds, thereby accelerating the overall drug development timeline.

• AI in Hospital Information System (HIS)

AI is being integrated into hospital information systems to optimize workflows, automate routine tasks, and improve the overall efficiency of healthcare delivery. This includes applications such as predictive analytics for patient outcomes and AI-driven resource allocation.

• AI in Medical Research

AI is transforming medical research by analyzing vast datasets to identify novel insights, patterns, and potential treatment avenues. This has the potential to accelerate the pace of medical discoveries and contribute to the development of more targeted and effective treatments.

• AI in Emergency Room and Surgery

In emergency room settings, AI is being utilized to analyse patient data in real-time, aiding healthcare professionals in making rapid and informed decisions. Additionally, AI is increasingly being integrated into surgical settings to assist surgeons with precision tasks and optimize surgical workflows.

• AI for the Treatment of Mental Health

AI is playing a significant role in the treatment of mental health conditions. Through natural language processing and sentiment analysis, AI-powered tools can assist in monitoring and analyzing patients’ mental health status, enabling more personalized and timely interventions.

Imagining the implications of the Future

As the utility of AI expands, questions arise regarding the legal implications of incorporating AI into clinical practice. The future of AI in medicine prompts considerations of the ethical, legal, and societal aspects of its integration into healthcare systems 

Conclusion

The evolution of AI in medicine has been marked by remarkable advancements in diagnostic capabilities, personalized treatment approaches, and streamlined healthcare processes. As AI continues to progress, its future implications hold immense promise for transforming the landscape of healthcare, ultimately leading to more precise, personalized, and efficient patient care.

The post Decoding the Journey of AI in Medicine: Outlining its Past and Imagining the Future first appeared on AITechTrend.