The molecular docking simulation is a key computational tool in modern drug discovery research that its predictive performance strongly depends on the employed scoring functions. Many recent studies have shown that the application of machine learning...
Journal of pharmacokinetics and pharmacodynamics
May 21, 2021
One of the objectives of Pharmacometry (PMX) population modeling is the identification of significant and clinically relevant relationships between parameters and covariates. Here, we demonstrate how this complex selection task could benefit from sup...
OBJECTIVES: We aimed to build a survival system by combining a highly-accurate machine learning (ML) model with explainable artificial intelligence (AI) techniques to predict distant metastasis in locoregionally advanced nasopharyngeal carcinoma (NPC...
IEEE transactions on bio-medical engineering
May 21, 2021
OBJECTIVE: When training machine learning models, we often assume that the training data and evaluation data are sampled from the same distribution. However, this assumption is violated when the model is evaluated on another unseen but similar databa...
IEEE transactions on bio-medical engineering
May 21, 2021
BACKGROUND: Despite recent significant progress in the development of automatic sleep staging methods, building a good model still remains a big challenge for sleep studies with a small cohort due to the data-variability and data-inefficiency issues....
Study of human disease remains challenging due to convoluted disease etiologies and complex molecular mechanisms at genetic, genomic, and proteomic levels. Many machine learning-based methods have been developed and widely used to alleviate some anal...
Cho et al. report deep learning model accuracy for tilted myopic disc detection in a South Korean population. Here we explore the importance of generalisability of machine learning (ML) in healthcare, and we emphasise that recurrent underrepresentati...
BACKGROUND: The aim of this study is to systematically review the literature to summarize the evidence surrounding the clinical utility of artificial intelligence (AI) in the field of mammography. Databases from PubMed, IEEE Xplore, and Scopus were s...
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