Artificial Intelligence
Keimyung University Dongsan Medical Center in South Korea has been testing AI technology to detect dementia and other neurodegenerative conditions, shares president Dr Chi-heum Cho.
AI & ML Intelligence
Dr. Eyal Zimlichman, chief innovation and transformation officer at Israel's Sheba Medical Center, says there will be much progress with these technologies – and health system IT leaders must be ready to adapt.
AI & ML Intelligence
Dr. Michael S. Barr, a veteran and a healthcare consultant, explains how SBAR – Situation, Background, Assessment and Recommendation – will bring C-level health system execs onboard for strategic artificial intelligence investments.
Dr. Samuel Browd of UW and Seattle Children's hospital, and the CMO at Proprio, discusses the questions he's hearing from patients about artificial intelligence in healthcare, and describes how AI is changing how he practices and performs surgery.
The hospital in Busan, which conducts 40,000 surgeries each year, has been developing various medical AI assistants through the government's Dr Answer project, says Dr Hoseok I, vice president and CIO at Pusan National University Hospital.
Success Stories & ROI
Impower therapists love the ambient listening technology, its COO reports. Artificial intelligence is helping them produce more clinically detailed notes, better comply with documentation submission and be more present with clients.
Etay Maor, Cato Networks' chief security strategist, will demonstrate jailbreaking, prompt injections and other real-world attacks at a HIMSS25 session focused on the use of artificial intelligence in healthcare.
An AI-powered "mission control centre" will streamline access to all data across Seoul National University Bundang Hospital to support clinicians' decision-making, says CIO Dr Seyoung Jung.
AI & ML Intelligence
Jennifer Stoll of OCHIN will speak at HIMSS25 on deploying artificial intelligence to benefit rural health systems and medically underserved communities.
New research from the University of Minnesota shows wide discrepancies, not just with artificial intelligence adoption, but with how well providers are equipped – financially and technically – to assess their AI tools for efficacy and integrity.