
AI model explains medical images to doctors
A new artificial intelligence model uses 23 million data triplets to explain its clinical decisions instead of acting as a black box.
Discover the newest research about AI innovations in 🧠LLM’s.

A new artificial intelligence model uses 23 million data triplets to explain its clinical decisions instead of acting as a black box.

Hospitals cannot share patient records, but a new federated framework allows AI models to learn from clinical notes across institutions without moving a single byte of raw data.

Standard AI models routinely invent patient data, but a new multi-layered architecture proves we can engineer clinical accuracy.

A new transformer model can simulate how a patient’s lab values will react to specific drugs before they are even prescribed.

Giving patients direct access to AI-translated medical records is a bold play to win the EHR wars, but it shifts a massive cognitive burden from doctors to software.

A new generative model beats traditional machine learning at predicting which discharged emergency patients will return to the hospital.

A new study shows that smart prompting makes cheap, small AI models triage patients just as safely as expensive ones.

Feeding raw medical data directly into clinical AI models might be degrading their performance without anyone noticing.

An attention-based AI model has mapped the genetic boundaries between neurological and psychiatric diseases using nothing but raw electronic health records.

A new AI model screens for painful spinal fractures using simple home videos instead of immediate, expensive hospital scans.