AI Reads Clinical Notes to Predict Recovery After Cardiac Arrest
A natural language processing model trained on clinical notes predicts neurologic outcome in comatose cardiac arrest survivors while exposing hidden ...
A natural language processing model trained on clinical notes predicts neurologic outcome in comatose cardiac arrest survivors while exposing hidden ...
A scoping review of 22 studies shows that EEG-measured mu and beta desynchronization during action observation therapy reliably tracks cortical ...
New EEG and thermal imaging evidence shows that theta/low-alpha oscillations in a frontoparietal-insular network integrate skin temperature signals into the ...
Researchers report that a random forest model combining EEG features with cerebral blood flow oscillations classified consciousness in severely brain-injured ...
A comprehensive review of 69 studies shows that machine learning and deep learning models can diagnose depression from EEG and ...
A 15-day supervised complete fasting study tracking event-related potentials in nineteen adults found that emotional reactivity shifts in two distinct ...
New EEG research shows that adolescents with depression report weaker self-compassion and show persistently elevated late positive potential amplitudes when ...
Researchers have built a machine learning model that detects major depressive disorder by mining higher-order transition rules in EEG microstate ...
A brain-inspired spiking neural network that filters and decodes EEG signals can detect mental fatigue in tower crane operators with ...
A multi-site EEG study finds that Parkinson's disease alters the timing of low-beta brain bursts while theta burst amplitude tracks ...
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© 2025 Scienmag - Science Magazine