Studies reveal AI tools in medicine can degrade accuracy and introduce new risks like watermark-induced hallucinations, eroding trust. This is accelerating a shift to on-premise deployment where institutions can control models and validate outputs locally.
A new study shows that watermarks on medical LLMs induce hallucinations, lexical corruption, and diagnostic errors. Standard benchmarks fail to catch these failures, creating a false sense of safety. The issue is critical for on-premise healthcare de...
Anthropic’s new science grant program isn’t just charity. It’s a signal that the company is paving the way for locally run models, where clinical data privacy is a must and the cloud can’t reach.
A multi-agent framework augments LLMs with an automatically built knowledge graph for sequential diagnosis. On clinical datasets, using backbones like DeepSeek-V3 and Llama-3.3, GraphDx lifts success rates from 50-68% to 79-93% and slashes test costs...
A 2025 American Medical Association survey finds 61% of physicians worry AI will worsen unjustified denials in health insurance prior authorization. While AI could speed up approvals, resistance is mounting, raising crucial questions about transparen...
Paris and Silicon Valley-based startup Raidium has deployed its AI-native imaging platform at Moffitt Cancer Center, replacing legacy radiomics applications. A signal about where clinical AI is heading, and what it demands from infrastructure.
