As artificial intelligence (AI) becomes increasingly capable of assisting with health care tasks, a new study by researchers at the Icahn School of Medicine at Mount Sinai has found that adding a brief safety reminder reduced potentially harmful choices by AI models in clinical scenarios. The study, published in the September 26 online issue of Communications Medicine [DOI: 10.1038/s43856-026-01933-8], a Nature Journal, also found that AI models can be influenced by the context and instructions surrounding a clinical decision. The findings, based on millions of outputs, suggest that how AI systems are prompted and guided may remain an important consideration in developing safe and reliable clinical applications, even as increasingly capable AI models and agents become better able to understand users’ intent without lengthy or comprehensive prompts.

American Heart Association Hypertension Scientific Sessions 2026 – Moderated Poster #TH125 - Three of the top four popular artificial intelligence (AI) tools – OpenAI’s ChatGPT, Microsoft’s Copilot and Perplexity AI – could not consistently identify if a home blood pressure monitor had passed clinical validation testing, with accuracy only 63% to 83% of the time. Google Gemini performed better but still provided incorrect responses about 10% to 15% of the time.

Training in AI skills improves the chances of women from underrepresented backgrounds being invited to job interviews, but not enough to eliminate the inequalities they face in the labour market, according to a new study.

New technology combines artificial intelligence and microscopy to screen cells at large scale.