This week, Abridge announced that its artificial intelligence listening documentation platform will be more widely distributed at the Mayo Clinic to improve patient care following its healthcare system review. Use of Google and others’ machine learning models is also increasing in areas such as drug repurposing and tracking and responding to infectious diseases, with announcements from the nonprofit Every Cure and Switchboard, MD.
Equipping nurses with ambient AI
After a rigorous evaluation of the clinical quality of Abridge’s AI environment documentation workflow for nurses, developed in partnership with Mayo Clinic and electronic health record provider Epic Systems, the company announced its new enterprise-wide agreement on Tuesday.
The expansion of the partnership will see the company connect approximately 2,000 Mayo Clinic physicians who serve more than one million patients annually with its AI-powered clinical documentation software.
“At Mayo Clinic, we are committed to deploying innovative AI platforms to improve the well-being of both physicians and deliver high-quality, patient-centered care,” said Dr. Amy Williams, executive dean of the health care system, said in a statement. .
“This collaboration aims to enhance our continued innovation and allows our physicians to focus on what matters most: our patients.”
Expanded access to ambient AI eases nurses’ administrative burdens, “ultimately empowering both physicians and nurses to focus more on targeted patient care,” said Dr. Shiv Rao, CEO and founder of Abridge.
He praised Mayo Clinic’s ethos for adopting high-quality AI innovations to advance healthcare using generative AI. He told me before Healthcare IT news that genAI can help recruit the next generation to work in healthcare by simplifying difficult and labor-intensive processes.
The clinic is a pioneer in AI, using large language models to improve many aspects of healthcare, such as using real-world data to advance precision medicine.
Using LLMS for predictions of off-label use
Every Cure announced Monday that it will leverage Google LLM for Google Cloud infrastructure and AI technologies, including Gemini 2.0, to accelerate life-saving discoveries and improve patient outcomes for diseases for which there are no effective therapies.
The nonprofit said in a statement that more than 300 million people worldwide suffer from diseases with no available treatments and that repurposing medicines can address this unmet need and help improve the affordability of treatments.
Computational biology platform Matrix will use Google tools to examine established safety profiles and analyze comprehensive data to validate new applications for existing drugs.
The company said the collaboration will focus on three use cases:
- Improving the accuracy of AI-driven drug repurposing predictions.
- Validation of predictions through accelerated preclinical testing and optimized clinical trials.
- Ensure global adoption of validated treatments.
“We are so excited about the potential of this partnership with Google Cloud to quickly scale the impact Every Cure can make on patients’ lives,” said Dr. David Fajgenbaum, co-founder and president of Every Cure, said in a statement. “We created Every Cure to treat patients with existing medications as quickly as possible and this partnership increases our ability to do this.”
Detecting infectious diseases with NLP
Switchboard, MD launched ThreatAware, which uses natural language processing and machine learning models to identify and prioritize potential disease-specific cases.
Developed with support from the Department of Health and Human Services, Administration for Strategic Preparedness and Response, and Biomedical Advanced Research and Development Authority, the system helps identify potential infectious disease risks early so physicians can quickly intervene in at-risk patients.
“Having a flexible and well-integrated system is essential for managing emerging health threats,” says Dr. Larry J. Anderson, professor at Emory University School of Medicine and former director of the Centers for Disease Control’s Division of Viral Diseases in the National Center for Vaccination and Respiratory Diseases, said a statement.
“In the event of new outbreaks, symptoms and data points can evolve quickly, and being able to quickly adapt and analyze those changes is critical to making informed decisions and supporting effective responses.”
Switchboard said AI does much more than identify and classify emerging infectious disease risks, by enabling healthcare organizations to quickly scale their response and better collaborate with public health authorities – a major opportunity for the emerging technology.
Developing infectious disease models requires numerous considerations, said Switchboard Technical Director Yuanda Zhu.
“The complexity of medical conditions, the need for expertly labeled training data, and the wide variation in how patients describe potential symptoms all require careful consideration,” she said in a statement.
“By working with a wide range of clinicians from around the world, who helped train and validate ThreatAware, we have created a system that adapts to real-world scenarios and delivers reliable, actionable insights.”
Andrea Fox is editor-in-chief of Healthcare IT News.
Email: afox@himss.org
Healthcare IT News is a HIMSS Media publication.