Autism Spectrum Disorder is a neuropsychiatric condition affecting 53 million children worldwide and for which early diagnosis is critical to the outcome of behavior therapies. Machine learning applied to features manually extracted from readily acce...
OBJECTIVE: Mortality following surgical resection of spinal tumors is a devastating outcome. Naïve Bayes machine learning algorithms may be leveraged in surgical planning to predict mortality. In this investigation, we use a Naïve Bayes classificatio...
Gas chromatography-mass spectrometry (GC-MS) is one of the major platforms for analyzing volatile compounds in complex samples. However, automatic and accurate extraction of qualitative and quantitative information is still challenging when analyzing...
BACKGROUND: Internet gaming disorder (IGD) is included in the DSM-5 as a provisional diagnosis. Whether IGD should be regarded as a disorder and, if so, how it should be defined and thresholded have generated considerable debate.
This study presents the combination of Raman spectroscopy with machine learning algorithms as a prospective diagnostic tool capable of detecting and monitoring relevant variations of pH and lactate as recognized biomarkers of several pathologies. The...
OBJECTIVES: We sought to develop a prediction score with data from the Vascular Quality Initiative (VQI) EVAR in efforts to assist endovascular specialists in deciding whether or not a patient is appropriate for short-stay discharge.
This study explores how the human brain solves the challenge of flicker noise in motion processing. Despite providing no useful directional motion information, flicker is common in the visual environment and exhibits omnidirectional motion energy whi...
Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall survival for these patients is usually perishing. However, a model with high accuracy for predicting the survival of NSCLC with BM is still lacking. Here,...
Neural networks : the official journal of the International Neural Network Society
Jun 5, 2020
In the real industrial production process, some minor faults are difficult to be detected by multivariate statistical analysis methods with mean and variance as detection indicators due to the aging equipment and catalyst deactivation. With structura...
Scandinavian journal of trauma, resuscitation and emergency medicine
May 27, 2020
BACKGROUND: The use of machine learning techniques to predict diseases outcomes has grown significantly in the last decade. Several studies prove that the machine learning predictive techniques outperform the classical multivariate techniques. We aim...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.