AIMC Topic: ROC Curve

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Unveiling new disease, pathway, and gene associations via multi-scale neural network.

PloS one Apr 6, 2020
Diseases involve complex modifications to the cellular machinery. The gene expression profile of the affected cells contains characteristic patterns linked to a disease. Hence, new biological knowledge about a disease can be extracted from these prof...
Humans Signal Transduction Transcriptome Models, Biological ROC Curve Neural Networks, Computer Gene Regulatory Networks Prognosis Disease Comorbidity Computational Biology
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Groundwater Potential Mapping Combining Artificial Neural Network and Real AdaBoost Ensemble Technique: The DakNong Province Case-study, Vietnam.

International journal of environmental research and public health Apr 4, 2020
The main aim of this study is to assess groundwater potential of the DakNong province, Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates Artificial Neural Networks (ANN) with RealAdaBoost (RAB) ensemble technique. F...
Vietnam Neural Networks, Computer Machine Learning ROC Curve Groundwater Water Resources
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Efficacy for Differentiating Nonglaucomatous Versus Glaucomatous Optic Neuropathy Using Deep Learning Systems.

American journal of ophthalmology Apr 2, 2020
PURPOSE: We sought to assess the performance of deep learning approaches for differentiating nonglaucomatous optic neuropathy with disc pallor (NGON) vs glaucomatous optic neuropathy (GON) on color fundus photographs by the use of image recognition.
Optic Nerve Diseases Photography Area Under Curve Optic Disk Visual Field Tests Algorithms Female Humans Intraocular Pressure Reproducibility of Results Neural Networks, Computer Male Glaucoma Deep Learning Sensitivity and Specificity ROC Curve
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Deep learning-based radiomic features for improving neoadjuvant chemoradiation response prediction in locally advanced rectal cancer.

Physics in medicine and biology Apr 2, 2020
Radiomic features achieve promising results in cancer diagnosis, treatment response prediction, and survival prediction. Our goal is to compare the handcrafted (explicitly designed) and deep learning (DL)-based radiomic features extracted from pre-tr...
Humans Female Male Neoadjuvant Therapy Rectal Neoplasms Middle Aged Chemoradiotherapy Deep Learning Diffusion Magnetic Resonance Imaging ROC Curve Treatment Outcome
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Cloud-based ECG monitoring using event-driven ECG acquisition and machine learning techniques.

Physical and engineering sciences in medicine Apr 1, 2020
An approach is proposed for the detection of chronic heart disorders from the electrocardiogram (ECG) signals. It utilizes an intelligent event-driven ECG signal acquisition system to achieve a real-time compression and effective signal processing an...
Cloud Computing Electrocardiography Support Vector Machine Humans Analog-Digital Conversion Area Under Curve Machine Learning Signal Processing, Computer-Assisted ROC Curve
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Automatic detection of tympanic membrane and middle ear infection from oto-endoscopic images via convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society Apr 1, 2020
Convolutional neural networks (CNNs), a popular type of deep neural network, have been actively applied to image recognition, object detection, object localization, semantic segmentation, and object instance segmentation. Accordingly, the applicabili...
Databases, Factual Reproducibility of Results Deep Learning ROC Curve Otitis Media Tympanic Membrane Neuroendoscopy Humans Neural Networks, Computer
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LEAP: Using machine learning to support variant classification in a clinical setting.

Human mutation Apr 1, 2020
Advances in genome sequencing have led to a tremendous increase in the discovery of novel missense variants, but evidence for determining clinical significance can be limited or conflicting. Here, we present Learning from Evidence to Assess Pathogeni...
Humans Machine Learning Cardiovascular Diseases Neoplasms ROC Curve Mutation, Missense Genomics Logistic Models Models, Genetic Models, Statistical Area Under Curve
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Augmented Intelligence Dermatology: Deep Neural Networks Empower Medical Professionals in Diagnosing Skin Cancer and Predicting Treatment Options for 134 Skin Disorders.

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...
ROC Curve Antiviral Agents Antifungal Agents Skin Glucocorticoids Deep Learning Clinical Competence Adolescent Image Interpretation, Computer-Assisted Datasets as Topic Photography Internship and Residency Feasibility Studies Dermatologists Skin Diseases Dermatology Female Skin Neoplasms Dermoscopy Aged Young Adult Adult Male Middle Aged Humans Anti-Bacterial Agents Drug Therapy, Computer-Assisted
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Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.

European radiology Mar 28, 2020
OBJECTIVES: We develop and validate a radiomics model based on multiparametric magnetic resonance imaging (MRI) in the classification of the pulmonary lesion and identify optimal machine learning methods.
Lung Diseases Multiparametric Magnetic Resonance Imaging Lung Humans Cohort Studies ROC Curve Support Vector Machine Young Adult Machine Learning Adult Retrospective Studies Male Female Middle Aged Aged
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HMMPred: Accurate Prediction of DNA-Binding Proteins Based on HMM Profiles and XGBoost Feature Selection.

Computational and mathematical methods in medicine Mar 28, 2020
Prediction of DNA-binding proteins (DBPs) has become a popular research topic in protein science due to its crucial role in all aspects of biological activities. Even though considerable efforts have been devoted to developing powerful computational ...
Amino Acids DNA-Binding Proteins ROC Curve Amino Acid Sequence Computational Biology Humans Markov Chains Support Vector Machine Machine Learning Databases, Protein Algorithms
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