Journal of the American Medical Informatics Association : JAMIA
Jun 1, 2020
OBJECTIVE: The goal of this study was to explore whether features of recorded and transcribed audio communication data extracted by machine learning algorithms can be used to train a classifier for anxiety.
BACKGROUND: Diabetes is a disease that affects the body's ability to produce or use insulin. A total of 425 million people are suffering from diabetes in the world. Of this, more than 16 million people live in the Africa Region, which is estimated to...
This study uses video and a pretrained deep convolutional neural network to analyze facial photoplethysmographic signals in detection of atrial fibrillation.
Journal of psychiatry & neuroscience : JPN
Jul 1, 2019
BACKGROUND: The development of diagnostic and prognostic tools for Alzheimer disease is complicated by substantial clinical heterogeneity in prodromal stages. Many neuroimaging studies have focused on case–control classification and predicting conver...
IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Jun 1, 2019
Rehabilitation robots can provide high intensity and dosage training or assist patients in activities of daily living and decrease physical strain on clinicians. However, the physical human robot interaction poses a major safety issue, as the close p...
The American journal of surgical pathology
Dec 1, 2018
Advances in the quality of whole-slide images have set the stage for the clinical use of digital images in anatomic pathology. Along with advances in computer image analysis, this raises the possibility for computer-assisted diagnostics in pathology ...
Restorative neurology and neuroscience
Jan 1, 2018
BACKGROUND: Robotic rehabilitation is a highly promising approach to recover lost functions after stroke or other neurological disorders. Unfortunately, robotic rehabilitation currently suffers from "motor slacking", a phenomenon in which the human m...
IMPORTANCE: Increased ability to quantify anatomical phenotypes across multiple organs provides the opportunity to assess their cumulative ability to identify individuals at greatest susceptibility for adverse outcomes.
In some evolutionary robotics experiments, evolved robots are transferred from simulation to reality, while sensor/motor data flows back from reality to improve the next transferral. We envision a generalization of this approach: a simulation-to-real...