Scott Mayer McKinney

TL;DR: A robust assessment of the AI system paves the way for clinical trials to improve the accuracy and efficiency of breast cancer screening and using a combination of AI and human inputs could help to improve screening efficiency.

TL;DR: It is shown that it is possible to predict an individual's ability to maintain sleep in the face of sound using spontaneous brain rhythms from electroencephalography (EEG), and that individuals who generated more sleep spindle production went on to exhibit higher tolerance for noise during a subsequent, noisy night of sleep.

TL;DR: Expert-level models for detecting clinically relevant chest radiograph findings were developed for this study by using adjudicated reference standards and with population-level performance estimation.

TL;DR: In this paper, the authors examined the cortical arousal responses during sleep to typical hospital noises by sound level and type and sleep stage, and found that sounds in NREM stage 3 were less likely to cause arousals than sounds in non-REM stage 2; however, the probability of arousal to sounds presented in REM sleep varied less by sound type and caused a greater and more sustained elevation of instantaneous heart rate.

TL;DR: It is concluded that mismatch was not attributable to commonly measured polysomnographic measures of fragmentation, and further insight is needed into the complex relationships between subjective perception of sleep and conventional, objective measurements.