By predicting brain pressure from routine heart and blood signals, a new deep learning model challenges the necessity of invasive skull-drilling in intensive care units.
A new deep learning model proves that artificial intelligence does not just mimic old diagnostic rules to spot deadly heart valve disease—it finds hidden signals doctors have been missing for decades.
A new machine learning tool measures eye gaze and facial expressions during autism evaluations, but its struggle to distinguish autism from other developmental conditions reveals the limits of automated diagnostics.
By ditching expensive gene sequencing for a simpler neural network and qPCR setup, researchers may have found a way to make early cancer screening practical for local clinics.
A new machine learning pipeline proves that algorithms can label millions of breathing mismatches without losing accuracy, bypassing the human expert bottleneck in intensive care.