
AI Predicts ADHD Years Before Diagnosis
Predictive algorithms are moving from administrative tools to clinical safety nets, flagging developmental risks before symptoms disrupt a child’s life.
Discover the newest research about AI innovations in 🤖 Machine Learning.

Predictive algorithms are moving from administrative tools to clinical safety nets, flagging developmental risks before symptoms disrupt a child’s life.

A new algorithm spots which diabetic patients will crash after surgery, shifting the focus from reactive emergency care to proactive recovery.

Standard automated ECG software often misses critical cardiac warning signs, but a new deep learning model trained on UK Biobank data proves we can do much better.

An AI giant is moving from writing software code to designing biological molecules, raising both commercial hopes and biosecurity alarms.

Dermatology algorithms are quietly biased against gender, but forcing them to look at actual skin lesions instead of demographic noise might finally fix the problem.

A new AI system called MedGenesis can compress years of clinical research into hours by autonomously generating hypotheses and analyzing patient data.

Using artificial intelligence to grade medical answers backfires because algorithms prefer long-winded fluff over actual clinical accuracy.

Automating cancer registries with artificial intelligence sounds like an easy win, but new data shows these models fail at the precise timelines crucial for tracking patient care.

A new deep learning model can locate dangerous heart arrhythmia targets without needing to trigger the life-threatening rhythm first.

Ambient clinical AI is no longer just a digital scribe; it is actively inserting itself into financial and medical decisions.