Researchers create first-of-its-kind index of evolving policy landscape around health care AI
Peer-Reviewed Publication
This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 26-Jun-2026 03:16 ET (26-Jun-2026 07:16 GMT/UTC)
New York, NY — [June 1, 2026] —As hospitals and health systems rapidly adopt artificial intelligence (AI) technologies, a new study by investigators at the Icahn School of Medicine at Mount Sinai finds that the policies governing health care AI are expanding quickly but remain fragmented across regulators, governments, and standards organizations. Their findings were published in today’s online issue of npj Digital Medicine [https://doi.org/10.1038/s41746-026-02734-y]. The researchers analyzed 240 health care AI-related policies published between 2016 and 2025 using their newly developed framework called the Health & AI Policy Index. The analysis found that oversight efforts are accelerating worldwide, though no single, unified framework currently exists to guide how AI should be deployed, monitored, and governed in clinical settings.
Metabolic dysfunction‐associated steatotic liver disease (MASLD) and intrapancreatic fat deposition (IPFD) are disorders associated with dysfunctional lipid metabolism and obesity. In a recent study, researchers have reviewed and compared the definition, causes, diagnostic methods, and emerging treatments of MASLD and IPFD that could help improve patients’ outcomes. In addition, they shed light on recent advances in artificial intelligence applications and presented personalized therapy integrated with the liver‐pancreas axis, providing novel insights for disease management.
AI-generated images are widespread on social media. Starting in August 2026, platforms will be required under the EU AI Act to label certain types of such content. A study by CISPA researcher Sandra Höltervennhoff investigates how users perceive these so-called AI labels and how they influence the credibility of information. The paper, “That’s another doom I haven’t thought about”: A User Study on AI Labels as a Safeguard Against Image-Based Misinformation, was presented at the Conference on Human Factors in Computing Systems (CHI 2026) and received an Honorable Mention.