The UK's National Health Service made waves by implementing Cera's fall prediction AI across its hospitals and home care programs. This tool analyzes patient movement patterns to alert staff before falls happen. Nurses report it helps them prioritize high-risk patients better.

OpenAI's new healthcare agent platform allows developers to create AI helpers that can perform web searches, analyze files, and complete tasks like scheduling follow-up appointments. Early testers say this could reduce paperwork for doctors by handling routine online research.

A surprising study found patients slightly preferred AI-generated doctor messages but felt less satisfied when told a computer helped write them. Researchers suggested using phrases like "written with automated tools" to maintain trust. This highlights the importance of transparent AI use in patient communications.

Medicare policy changes now support AI-powered home care through better payment for virtual checkups and remote monitoring. New wearable devices can track blood pressure changes and alert doctors about potential heart issues before emergencies occur.

The US government's AI Task Force report recommended boosting AI training for medical staff while creating clearer rules for insurance coverage of AI services. It specifically mentioned improving cancer detection algorithms and using AI to match patients with clinical trials.

International experts released the FUTURE-AI guidelines to make medical AI safer and fairer. The rules require systems to work equally well for all patient groups and explain their decisions in simple terms. Hospitals in 50 countries helped create these standards.

Drug companies are breaking away from copycat medicines by using AI to discover novel targets. For example, Insilico Medicine identified a new gene therapy approach for heart disease using machine learning models trained on protein structures.

Some hospitals struggled with AI transcription errors where systems invented false symptoms or test results. One clinic stopped using OpenAI's Whisper for patient notes after finding made-up details about medication allergies. Experts warn all AI medical tools need human checks.

In Kentucky, researchers are testing fuzzy logic AI that understands vague descriptions like "sometimes dizzy" to improve diabetes care. This approach helps capture patient experiences that don't fit yes/no questionnaires.

Billing departments saw early success with AI tools that catch insurance claim errors before submission. A pilot program reduced denied claims by 15% by spotting missing information in real-time. However, many hospitals still lack staff trained to use these systems effectively.

Looking ahead, Epic Systems plans deeper AI integration in medical records to automatically flag care gaps and suggest treatments. Their approach uses hospital-specific data to make recommendations more precise than generic AI models.