A picture may be worth a thousand words, but still... they both have a lot of work to do to catch up to BiomedGPT.

Covered recently in the prestigious journal Nature Medicine, BiomedGPT is a new a new type of artificial intelligence (AI) designed to support a wide range of medical and scientific tasks.

Published in JAMA Network Open, a collaborative team of researchers from the University of Minnesota Medical School, Stanford University, Beth Israel Deaconess Medical Center and the University of Virginia studied how well doctors used GPT-4 - an artificial intelligence (AI) large language model system - for diagnosing patients.

The study was conducted with 50 U.S.-licensed physicians in family medicine, internal medicine and emergency medicine.

Scientists from Cleveland Clinic and Cornell University have designed a publicly-available software and web database to break down barriers to identifying key protein-protein interactions to treat with medication.

The computational tool is called PIONEER (Protein-protein InteractiOn iNtErfacE pRediction). Researchers demonstrated PIONEER's utility by identifying potential drug targets for dozens of cancers and other complex diseases in a recently published Nature Biotechnology article.

A team of researchers says it has developed the first wearable camera system that, with the help of artificial intelligence (AI), detects potential errors in medication delivery.

In a test whose results were published today, the video system recognized and identified, with high proficiency, which medications were being drawn in busy clinical settings.

A pilot study led by researchers at University of California San Diego School of Medicine found that advanced artificial intelligence (AI) could potentially lead to easier, faster and more efficient hospital quality reporting while retaining high accuracy, which could lead to enhanced health care delivery.

The study results, published in the October 21, 2024 online edition of the New England Journal of Medicine (NEJM) AI,

The use of artificial intelligence (AI) in hospitals and patient care is steadily increasing. Especially in specialist areas with a high proportion of imaging, such as radiology, AI has long been part of everyday clinical practice. However, the question of the extent to which AI actually influences workflows in a clinical setting remains largely unanswered. Researchers at the University Hospital Bonn (UKB) and the University of Bonn have therefore conducted a comprehensive analysis of existing studies on the effect of AI.

Ludwig Cancer Research scientists have developed a full, start-to-finish computational pipeline that integrates multiple molecular and genetic analyses of tumors and the specific molecular targets of T cells and harnesses artificial intelligence algorithms to use its output to design personalized cancer vaccines for patients.

The design, validation and comparative assessment of this computational suite, NeoDisc, are detailed in the current issue of Nature Biotechnology in a publication led by Florian Huber and Michal Bassani-Sternberg of the Lausanne Branch of the Ludwig Institute for Cancer Research.