This week, Abridge announced it will be distributing its artificial intelligence-powered listening documentation platform more broadly at the Mayo Clinic to improve the health system’s post-assessment patient care. It’s clear that the use of machine learning models from Google and others is also accelerating in areas such as drug repurposing and infectious disease, according to an announcement by the nonprofit organization Every Cure and Switchboard, MD. Monitor and respond.
Delivering ambient AI to nurses
Following a rigorous clinical records quality assessment evaluation of Abridge’s AI ambient documentation workflow for nurses, developed in partnership with Mayo Clinic and electronic medical records vendor Epic Systems, the company announced Tuesday a new companywide agreement. announced.
Through the expanded partnership, the company will begin to connect its AI-powered clinical documentation software with approximately 2,000 Mayo Clinic clinicians who serve more than 1 million patients annually.
“At Mayo Clinic, we are committed to leveraging our innovative AI platform to improve the health of our clinicians and provide high-quality, patient-centered care,” said Amy, clinical director of the health system. Dr. Williams said in a statement. .
“This partnership is designed to strengthen our continued innovation and allow clinicians to focus on what matters most – their patients.”
Expanding access to ambient AI will reduce the administrative burden on nurses, “ultimately freeing up both physicians and nurses to focus more on intensive patient care,” says Abridge. added Dr. Shiv Rao, CEO and Founder.
He praised Mayo Clinic’s ethos of deploying high-quality AI innovations to leverage generative AI to advance healthcare. He previously told Healthcare IT News that genAI can help recruit the next generation of healthcare industry workers by simplifying difficult and labor-intensive processes.
The clinic is a pioneer in AI, using large-scale language models to improve many aspects of healthcare delivery, including using real-world data to advance precision medicine.
Predicting off-label use using LLM
Every Cure announced Monday that it will use Google LLM for its Google Cloud infrastructure and AI technologies, including Gemini 2.0, to accelerate life-saving discoveries and improve patient outcomes for diseases without effective treatments. .
The nonprofit organization said in a statement that more than 300 million people worldwide suffer from diseases for which there are no available treatments, and drug repurposing will address this unmet need and make treatments more affordable. He said that it will help improve the
Matrix, a computational biology platform, uses Google tools to examine established safety profiles and analyze extensive data to validate new uses for existing medicines.
The company said the partnership will focus on three use cases:
Improving the accuracy of drug reuse predictions with AI. Validate predictions through accelerated preclinical testing and optimized clinical trials. Ensure global adoption of validated treatments.
“Every Cure’s co-founder and president, Dr. David Fajgenbaum, said in a statement: “We are very excited about the potential for Every Cure to quickly scale up its impact on patient lives through our collaboration with Google Cloud.” “To treat patients on existing medications as quickly as possible. , we developed Every Cure, and this collaboration significantly strengthens our ability to make this happen.”
Infectious disease detection using NLP
Maryland Switchboard launches ThreatAware, which uses natural language processing and machine learning models to identify and prioritize potential disease-specific cases.
The system was developed with support from the Department of Health and Human Services, Office of Strategic Preparedness and Response, and Biomedical Advanced Research and Development Authority to help identify potential infectious disease risks early and help clinicians identify at-risk patients. can help you intervene quickly.
“Having flexible and well-integrated systems in place is essential to addressing emerging health threats,” said Larry, professor of medicine at Emory University and former director of the Division of Viral Diseases at the National Centers for Disease Control. says Dr. J. Anderson. The Center for Immunization and Respiratory Diseases said in a statement.
“In the case of new outbreaks, symptoms and data points can evolve rapidly, and being able to quickly adapt and analyze those changes will help make informed decisions and support an effective response.” It is important for
Switchboard believes that AI is a huge enabler for emerging technologies, not only for identifying and classifying the risks of emerging infectious diseases by enabling healthcare organizations to quickly scale up responses and strengthen collaboration with public health agencies. He says it’s an opportunity.
According to Yuanda Zhu, director of engineering at Switchboard, developing models of infectious diseases requires many considerations.
“The complexity of the disease state, the need for professionally labeled training data, and the wide variation in how patients describe potential symptoms all require careful consideration,” she said in a statement. .
“By collaborating with a wide range of clinicians around the world who helped train and validate ThreatAware, we created a system that adapts to real-world scenarios and provides reliable and actionable insights.”
Andrea Fox is a senior editor at Healthcare IT News.
Email: afox@himss.org
Healthcare IT News is a publication of HIMSS Media.
