Does AI know when to say "no"? New study reveals AI chatbots recognize unnecessary medical tests, but stumble where human doctors disagree
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Updates every hour. Last Updated: 30-Oct-2026 21:16 ET (31-Oct-2026 01:16 GMT/UTC)
Many older patients with heart failure survive hospitalization but lose independence within a year after discharge. Researchers from Japan developed a machine learning model using physical function and clinical data to predict this risk. The model outperformed a standard frailty screening tool and identified a group with low mortality but high functional decline. The findings could help clinicians prioritize rehabilitation and discharge support for patients most likely to lose independence after discharge and improve care.
Led by NYU Langone Health psychiatrists and engineers, the study explored a technique called transcranial ultrasound stimulation in 10 men and women with schizophrenia or schizoaffective disorder who had ongoing symptoms despite drug treatment. The approach uses gentle, focused sound waves to boost or suppress brain cell activity in regions that are otherwise hard to access without surgery or other invasive procedures.
The International Society for Stem Cell Research (ISSCR) today opens its international symposium celebrating the 20th anniversary of induced pluripotent stem (iPS) cell technology, bringing together scientists, clinicians, and innovators from around the world to reflect on two decades of transformative discoveries and explore the future of stem cell research and regenerative medicine.
The three-day symposium, held Oct. 20–22 in Kyoto, Japan, is organized in partnership with the Center for iPS Cell Research and Application (CiRA) and co-sponsored by the Japanese Society for Regenerative Medicine (JSRM).
The extraordinary response to the symposium underscores the strength and momentum of stem cell science worldwide. Registration reached capacity twice, even after the ISSCR expanded the meeting to a larger venue to accommodate growing demand. This remarkable level of interest reflects both the profound impact of iPSC technology over the past two decades and the expanding opportunities ahead, from fundamental discoveries in human biology to advances in disease modeling, drug discovery, clinical translation, and the development of stem cell-based therapies.