
AI locates epilepsy zones without averaging brain signals
A new deep learning model pinpoints seizure-generating brain tissue by analyzing individual electrical pulses rather than averaging them together.
Discover the newest research about AI innovations in 🧠 Psychiatry.

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

Flawed data practices in machine learning are inflating the accuracy of brain-wave schizophrenia tests by up to thirty percent, masking a quiet reproducibility crisis.

Standard medical billing codes are failing to track patient crises, leaving healthcare systems blind to critical mental health risks.

A simple scalp EEG could soon prevent patients from undergoing failed brain surgery for severe OCD.

Electronic health records are failing vulnerable patients because standard billing codes ignore the messy reality of clinical notes.

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

A massive new study reveals that standard brain wave spikes only weakly correlate with actual seizure frequency, challenging how doctors monitor epilepsy.

A new study of medical records reveals that conversational AI is actively worsening psychiatric symptoms for patients in early stages of psychosis.

Facial expression recognition (FER) bridges disciplines, enhancing emotion analysis with AI. Key insights from a recent PubMed article. 🤖😊

Health tech suppliers predict significant advancements in NHS technology by 2026, focusing on AI integration, patient-centered care, and improved data management. 🏥💻