Clinical pharmacology and therapeutics
Feb 27, 2020
Dihydropyrimidine dehydrogenase (DPD)-deficient patients might only become aware of their genotype after exposure to dihydropyrimidines, if testing is performed. Case reports to pharmacovigilance databases might only contain phenotypical manifestatio...
Journal of chemical information and modeling
Feb 27, 2020
Unannotated gene sequences in databases are increasing due to sequencing advances. Therefore, computational methods to predict functions of unannotated genes are needed. Moreover, novel enzyme discovery for metabolic engineering applications further ...
Neural networks : the official journal of the International Neural Network Society
Feb 26, 2020
Rectified activation units make an important contribution to the success of deep neural networks in many computer vision tasks. In this paper, we propose a Parametric Deformable Exponential Linear Unit (PDELU) and theoretically verify its effectivene...
Over the past decade, there has been a groundswell of research interest in computer-based methods for objectively quantifying fibrotic lung disease on high resolution CT of the chest. In the past 5 years, the arrival of deep learning-based image anal...
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
Feb 25, 2020
BACKGROUND: Relatives of patients with bladder cancer have been shown to be at increased risk for kidney, lung, thyroid, and cervical cancer after correcting for smoking-related behaviors that may concentrate in some families. We demonstrate a novel ...
Statistical knowledge about many patients could be exploited using machine learning to provide supporting information to otolaryngologists and other hearing health care professionals, but needs to be made accessible. The Common Audiological Function...
BACKGROUND: Accurate prediction of operative transfusions is essential for resource allocation and identifying patients at risk of postoperative adverse events. This research examines the efficacy of using artificial neural networks (ANNs) to predict...
Artificial neural network (ANN) models can be trained to simulate the dynamic behavior of biological systems. In the present study, an ANN model was developed upon multilayer perceptron neural network architecture with 23-20-1 configuration to predic...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Feb 20, 2020
Highlighting the risk of biases in radiomics-based models will help improve their quality and increase usage as decision support systems in the clinic. In this study we use machine learning-based methods to identify the presence of volume-confounding...
Computer methods and programs in biomedicine
Feb 19, 2020
BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) is the most common cardiac arrhythmia in clinical practice, having been recognized as a true cardiovascular epidemic. In this paper, a new methodology for Computer Aided Diagnosis of AF based on a sp...
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