Smartphones screen children for autism using eye tracking
A new smartphone eye-tracking tool could bypass long clinic waitlists by screening children for autism at home.
Discover the newest research about AI innovations in 🧠Neuroscience.
A new smartphone eye-tracking tool could bypass long clinic waitlists by screening children for autism at home.

A new deep learning model pinpoints seizure-generating brain tissue by analyzing individual electrical pulses rather than averaging them together.

A new proteomic analysis reveals why Parkinson’s drug trials keep failing despite using biologically pure patient groups.

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

Pairing untrained staff with artificial intelligence could solve the specialist shortage in operating rooms.

A simple anatomical marker combined with machine learning could change how clinicians predict long-term recovery after a severe brain bleed.

By analyzing continuous vital signs in the air, machine learning can identify traumatic brain injuries before the helicopter even lands.

Measuring a single protein has been the gold standard for tracking ALS, but a new multi-protein signature suggests we have been missing the bigger biological picture.

A new nine-protein blood signature outperforms traditional clinical models and single-marker tests in predicting how fast ALS progresses.

Deep learning models trained to spot Alzheimer’s disease are systematically blind to atypical forms of brain decay, raising doubts about their readiness for real-world clinics.