Predicting immunogenicity for biotherapies using patient and drug-related factors represents nowadays a challenging issue. With the growing ability to collect massive amount of data, machine learning algorithms can provide efficient predictive tools....
Quasi-stable electrical fields in the EEG, called microstates carry information on the dynamics of large scale brain networks. Using machine learning techniques, we explored whether abnormalities in microstates can be used to classify patients with s...
Affective communication, communicating with emotion, during face-to-face communication is critical for social interaction. Advances in artificial intelligence have made it essential to develop affective human-virtual agent communication. A person's b...
BACKGROUND: Recent advances in kernel-based Deep Learning models have introduced a new era in medical research. Originally designed for pattern recognition and image processing, Deep Learning models are now applied to survival prognosis of cancer pat...
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Apr 2, 2020
OBJECTIVE: Significant interscorer variability is found in manual scoring of arousals in polysomnographic recordings (PSGs). We propose a fully automatic method, the Multimodal Arousal Detector (MAD), for detecting arousals.
International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
Apr 2, 2020
BACKGROUND: There are limited data about Xpert-Ultra performance in different settings, in HIV-infected persons, in those with a history of previous TB, and with trace readouts.
International journal of legal medicine
Apr 1, 2020
Staging third molar development is commonly used for age assessment in sub-adults. Current staging techniques are, at most, semi-automated and rely on manual interactions prone to operator variability. The aim of this study was to fully automate the ...
International journal of injury control and safety promotion
Apr 1, 2020
The quality of vehicular collision data is crucial for studying the relationship between injury severity and collision factors. Misclassified injury severity data in the crash dataset, however, may cause inaccurate parameter estimates and consequentl...
This study aimed to screen for thyroid dysfunction using Raman spectroscopy combined with an improved support vector machine (SVM). In spectral analysis, in order to further improve the classification accuracy of the SVM algorithm model, a genetic pa...
The Journal of investigative dermatology
Mar 31, 2020
Although deep learning algorithms have demonstrated expert-level performance, previous efforts were mostly binary classifications of limited disorders. We trained an algorithm with 220,680 images of 174 disorders and validated it using Edinburgh (1,3...
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