Healthcare AI News 3/13/24

News

Sixteen large health systems and Microsoft form the Trustworthy and Responsible AI Network (TRAIN), which will share best practices, register the use of AI in clinical settings, provide AI outcomes measurements, and facilitate creation of a federated national AI outcomes registry. The group will work with OCHIN and TruBridge to make sure that all organizations, regardless of resources, can benefit from TRAIN’s work. The recently formed Coalition for Health AI (CHAI) is a partner and says that TRAIN will operationalize its principles in health systems.

Google launches Google Cloud Vertex Search for Healthcare, a set of search-and-answer tools that integrate with its MedLM, Healthcare Data Engine and Cloud Healthcare FHIR APIs. It offers medically-tuned search of EHR data for clinician presentation, configurable cloud APIs, the ability to answer clinician questions while understanding medical terminology, and providing links to source data points to provide transparency.

The government of China is working with private companies to develop a medically focused AI chatbot based on Meta’s Llama 2.0. It is testing an AI assistant model for neurosurgeons at seven hospitals in Beijing. The CARES Copilot 1.0 was trained on medical literature and can process images, audio, text, MRI, ultrasounds, and CT scans.

Microsoft previews healthcare-specific safeguards for Azure AI Health Bot services that integrate with Copilot Studio to allow healthcare organizations to develop their own copilots.

Business

Symplr announces SymplrAI, which will offer healthcare efficiency tools via Amazon Web Services AI/ML.

Peter Thiel-backed Cognition AI unveils Devin, an AI-powered software engineer that can generate, debug, and deploy code for websites and videos from a single command. It has its own command line, code editor, and browser.

Amazon Web Services lists the generative AI solutions that its healthcare customers have created:

• Digital pathology (Philips).
• Phone-based, voice-enabled progress note generation (Pieces Technologies).
• Hospital operations efficiency (Symplr).
• Enterprise imaging (Konica Minolta).

Biotech startup Insilico Medicine describes how it used its AI platform to create a drug candidate for idiopathic pulmonary fibrosis that is undergoing Phase II clinical trials. The company says the process took 2.5 years versus the six years that would have been needed without AI. The company used biology AI to discover the drug, then generated the molecule using chemistry AI.

Research

In England, University of Oxford researchers warn clinicians that using ChatGPT and Bard to create care plans could compromise patient privacy or mislead users with incorrect information.

In Israel, Sheba Medical Center researchers develop an AI platform to help mental health professionals diagnose and manage conditions efficiently, concluding that its diagnostic accuracy is comparable to that of experience psychiatrists.

A study finds that large language models can translate discharge summaries into readable, patient-friendly language, which helps providers comply with requirements to give patients immediate access to their discharge notes. However, the authors found examples of key information being omitted, most often history of present illness and procedures, which they attribute to prompt engineering that optimized readability in the form of shorter documents.

Other

CommonSpirit Health EVP/CIO Daniel Barchi, MS says that healthcare’s adoption of AI should follow the Maslow’s Hierarchy of Needs in first being applied to technical needs, then moved up the triangle to improve healthcare efficiency and safety. (click graphic to enlarge)

Contacts

Mr. H, Lorre, Jenn, Dr. Jayne.
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