Modeling discrete phenotypic traits for either ancestral character state reconstruction or morphology-based phylogenetic inference suffers from ambiguities of character coding, homology assessment, dependencies, and selection of adequate models. Thes...
OBJECTIVES: Artificial Intelligence (AI) offers significant potential for improving healthcare. This paper discusses how an "open science" approach to AI tool development, data sharing, education, and research can support the clinical adoption of AI ...
European journal of cancer (Oxford, England : 1990)
Jul 1, 2019
The way we categorise and classify cancer types dictates not only the way we diagnose and treat patients but also many of our decisions on biomarker and drug development. In addition, cancer taxonomy proves the ground truth for future discoveries in ...
Neural networks : the official journal of the International Neural Network Society
Jun 1, 2019
Learning an effective visual classifier from few labeled samples is a challenging problem, which has motivated the multi-source adaptation scheme in machine learning. While the advantages of multi-source adaptation have been widely recognized, there ...
Neural networks : the official journal of the International Neural Network Society
Jun 1, 2019
Twin support vector machine (TWSVM) is a classical and effective classifier for binary classification. However, its robustness cannot be guaranteed due to the utilization of squared L2-norm distance that can usually exaggerate the influence of outlie...
We show that Cohen's Kappa and Matthews Correlation Coefficient (MCC), both extended and contrasted measures of performance in multi-class classification, are correlated in most situations, albeit can differ in others. Indeed, although in the symmetr...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2019
Accurately estimating performance accuracy of machine learning classifiers is of fundamental importance in biomedical research with potentially societal consequences upon the deployment of bestperforming tools in everyday life. Although classificatio...
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2018
OBJECTIVES: Scoring laboratory polysomnography (PSG) data remains a manual task of visually annotating 3 primary categories: sleep stages, sleep disordered breathing, and limb movements. Attempts to automate this process have been hampered by the com...
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2018
OBJECTIVE: Develop an approach, One-class-at-a-time, for triaging psychiatric patients using machine learning on textual patient records. Our approach aims to automate the triaging process and reduce expert effort while providing high classification ...
Recent advances in machine learning allow faster training, improved performance and increased interpretability of classification techniques. Consequently, their application in neuroscience is rapidly increasing. While classification approaches have p...