This week, Abridge announced that its AI-powered listening and documentation platform will be rolled out more widely at Mayo Clinic to improve patient care after an assessment of the health care system. Announcements from nonprofits Every Cure and Switchboard, M.D. make it clear that the employ of Google and other machine learning models is also accelerating in areas like drug repurposing and infectious diseases surveillance and response.
Providing nurses with an AI environment
Following a stringent quality assessment of Abridge’s clinical documentation workflow for AI environment documentation for nurses, developed in cooperation with Mayo Clinic and electronic health record provider Epic Systems, the company announced a up-to-date enterprise-wide agreement on Tuesday.
With the expansion of the partnership, the company will begin connecting approximately 2,000 Mayo Clinic physicians serving more than one million patients annually with its AI-powered clinical documentation software.
“At Mayo Clinic, we are committed to leveraging innovative artificial intelligence platforms to improve the well-being of both physicians and provide high-quality, patient-centered care,” Dr. Amy Williams, dean of practice for the health system, said in a statement .
“This collaboration is designed to enhance our ongoing innovation and enable our physicians to focus on what matters most – our patients.”
Expanded access to ambient AI reduces nurses’ administrative burden, “ultimately enabling both physicians and nurses to devote more attention to patient care,” added Dr. Shiv Rao, CEO and founder of Abridge.
He credited Mayo Clinic’s ethos of implementing high-quality AI innovations to advance health care through the employ of generative AI. He has previously said that genAI could support recruit the next generation to work in the healthcare industry by simplifying complex and labor-intensive processes.
The clinic is a pioneer in artificial intelligence, using enormous language models to improve many aspects of healthcare delivery, such as using real-world data to improve precision medicine.
Using LLM to predict off-label uses
Every Cure announced Monday that it will employ Google LLM across Google Cloud infrastructure and artificial intelligence technologies, including Gemini 2.0, to accelerate life-saving discoveries and improve patient outcomes for diseases that lack effective therapies.
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 that drug repurposing can address this unmet need and support improve the affordability of treatments.
The Matrix computational biology platform will employ Google tools to examine established safety profiles and analyze affluent data to validate up-to-date uses for existing drugs.
The company said the collaboration will focus on three employ cases:
- Improving the accuracy of AI-based drug repurposing predictions.
- Validation of predictions through accelerated preclinical testing and optimized clinical trials.
- Ensuring global adoption of approved treatments.
“We are very excited about the potential of this partnership with Google Cloud to rapidly expand the impact Every Cure can have on patients’ lives,” Dr. David Fajgenbaum, co-founder and president of Every Cure, said in a statement. “We created Every Cure to treat patients with existing medicines as quickly as possible, and this collaboration expands our capabilities to do so.”
Detecting infectious diseases using NLP
Switchboard, MD has launched ThreatAware technology, 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, the Strategic Preparedness and Response Administration and the Office of Biomedical Advanced Research and Development, the system helps identify potential infectious disease risks early to enable physicians to quickly intervene in at-risk patients.
“Having a flexible and well-integrated system is essential to managing emerging health threats,” Dr. Larry J. Anderson, professor at Emory University School of Medicine and former director of the Division of Viral Diseases at the Centers for Disease Control’s National Center for Immunization and Respiratory Diseases, said in a statement.
“In new outbreaks, symptoms and data points can evolve rapidly, and the ability to quickly adapt and analyze these changes is critical to making informed decisions and supporting effective responses.”
Switchboard said AI can do much more than just identify and classify emerging infectious disease risks, enabling healthcare organizations to rapidly scale responses and better collaborate with public health agencies, representing a major opportunity for the emerging technology.
According to Yuanda Zhu, Switchboard’s chief technology officer, developing infectious disease models requires many considerations.
“The complexity of conditions, the need for expertly labeled training data, and the wide variation in how patients describe potential symptoms require careful consideration,” she said in a statement.
“By collaborating with a wide range of clinicians from around the world who have helped train and validate ThreatAware, we have created a system that adapts to real-world scenarios and delivers reliable, actionable insights.”