
Smartphones and LLMs Detect Huntington’s Disease
By feeding raw smartphone eye-tracking data into off-the-shelf language models, researchers bypassed the need for custom medical AI to spot Huntington’s disease.
Discover the newest research about AI innovations in 🧠LLM’s.

By feeding raw smartphone eye-tracking data into off-the-shelf language models, researchers bypassed the need for custom medical AI to spot Huntington’s disease.

Regulators are clearing the path for AI that writes its own clinical notes, shifting the technology from a simple second pair of eyes to an active administrative partner.

A new language model attempts to solve a major diagnostic bias by separating normal hormonal transitions from actual viral damage in women.

Hiring a commercial AI to read breast cancer biopsies does not just introduce errors; it forces clinicians to choose which specific flavor of diagnostic failure they can tolerate.

Automated translation of complex radiology scans can finally bypass the medical jargon barrier, but only if radiologists remain the ultimate gatekeepers.

A new study shows that off-the-shelf language models can reconstruct complex patient histories from messy clinical notes without manual human labeling.

A new clinical trial shows that while generative AI catches more blood clot risks than human doctors, its tendency to miss narrative details means it cannot fly solo.

An agentic AI system reviewed hospital readmissions as accurately as human doctors for a fraction of the cost, but the real revelation is how much clinicians disagree with each other.

A new study shows that small, locally hosted AI models can clean up messy clinical text better than expected, without risking patient privacy.

A new clinical pilot shows that letting an AI interview patients before they see a surgeon slashes consultation times while actually improving data quality.