AIMC Topic:
ROC Curve

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A comparative study on feature selection for a risk prediction model for colorectal cancer.

Computer methods and programs in biomedicine Jun 4, 2019
BACKGROUND AND OBJECTIVE: Risk prediction models aim at identifying people at higher risk of developing a target disease. Feature selection is particularly important to improve the prediction model performance avoiding overfitting and to identify the...
Databases, Factual Computer Simulation Colorectal Neoplasms Risk Assessment ROC Curve Support Vector Machine Area Under Curve Spain Computer Graphics Humans Neural Networks, Computer Software
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Error Tolerance of Machine Learning Algorithms across Contemporary Biological Targets.

Molecules (Basel, Switzerland) Jun 4, 2019
Machine learning continues to make strident advances in the prediction of desired properties concerning drug development. Problematically, the efficacy of machine learning in these arenas is reliant upon highly accurate and abundant data. These two l...
Models, Biological Machine Learning Molecular Targeted Therapy Algorithms Humans Reproducibility of Results Neural Networks, Computer Biomarkers, Tumor Drug Discovery Antineoplastic Agents ROC Curve Bayes Theorem Workflow
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Machine Learning Models Combined with Virtual Screening and Molecular Docking to Predict Human Topoisomerase I Inhibitors.

Molecules (Basel, Switzerland) Jun 4, 2019
In this work, random forest (RF), support vector machine, k-nearest neighbor and C4.5 decision tree, were used to establish classification models for predicting whether an unknown molecule is an inhibitor of human topoisomerase I (Top1) protein. All ...
Algorithms Computer Simulation Reproducibility of Results Molecular Docking Simulation ROC Curve Humans Machine Learning Molecular Structure Molecular Dynamics Simulation Quantitative Structure-Activity Relationship Topoisomerase I Inhibitors
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Predicting Inpatient Payments Prior to Lower Extremity Arthroplasty Using Deep Learning: Which Model Architecture Is Best?

The Journal of arthroplasty Jun 3, 2019
BACKGROUND: Recent advances in machine learning have given rise to deep learning, which uses hierarchical layers to build models, offering the ability to advance value-based healthcare by better predicting patient outcomes and costs of a given treatm...
Infant, Newborn Aged Young Adult Adult Male Humans Neural Networks, Computer Databases, Factual Female Child, Preschool Child ROC Curve Lower Extremity Inpatients Middle Aged Infant Deep Learning Adolescent Orthopedic Procedures Orthopedics Outcome Assessment, Health Care Arthroplasty, Replacement, Knee New York Arthroplasty, Replacement, Hip
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Deep Learning for the Radiographic Detection of Apical Lesions.

Journal of endodontics Jun 1, 2019
INTRODUCTION: We applied deep convolutional neural networks (CNNs) to detect apical lesions (ALs) on panoramic dental radiographs.
Neural Networks, Computer Sensitivity and Specificity Deep Learning ROC Curve Tooth
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Development and Validation of Deep Learning Models for Screening Multiple Abnormal Findings in Retinal Fundus Images.

Ophthalmology May 31, 2019
PURPOSE: To develop and evaluate deep learning models that screen multiple abnormal findings in retinal fundus images.
Datasets as Topic Sensitivity and Specificity Deep Learning Retinal Diseases Female Cross-Sectional Studies Humans Aged ROC Curve Male Neural Networks, Computer Aged, 80 and over Area Under Curve Middle Aged Machine Learning Adult Fundus Oculi Algorithms Image Interpretation, Computer-Assisted
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Development and Validation of a Bayesian Network Method to Detect External Beam Radiation Therapy Physician Order Errors.

International journal of radiation oncology, biology, physics May 31, 2019
PURPOSE: To investigate a Bayesian network (BN)-based method to detect errors in external beam radiation therapy physician orders.
Algorithms Simulation Training Neoplasms Medical Errors Cohort Studies Radiotherapy Setup Errors False Positive Reactions ROC Curve Technology, Radiologic Radiologists Radiotherapy Dosage Humans Bayes Theorem Organ Specificity Radiotherapy Planning, Computer-Assisted Neural Networks, Computer Dose Fractionation, Radiation Datasets as Topic Radiotherapy, Image-Guided False Negative Reactions
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Prediction of Nephropathy in Type 2 Diabetes: An Analysis of the ACCORD Trial Applying Machine Learning Techniques.

Clinical and translational science May 31, 2019
Applying data mining and machine learning (ML) techniques to clinical data might identify predictive biomarkers for diabetic nephropathy (DN), a common complication of type 2 diabetes mellitus (T2DM). A retrospective analysis of the Action to Control...
Data Mining Humans Machine Learning ROC Curve Biomarkers Risk Factors Diabetes Mellitus, Type 2 Female Diabetic Nephropathies Sensitivity and Specificity Models, Theoretical Male Middle Aged Incidence
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Deep learning facilitates the diagnosis of adult asthma.

Allergology international : official journal of the Japanese Society of Allergology May 30, 2019
BACKGROUND: We explored whether the use of deep learning to model combinations of symptom-physical signs and objective tests, such as lung function tests and the bronchial challenge test, would improve model performance in predicting the initial diag...
Female Asthma Male Deep Learning ROC Curve Logistic Models Models, Theoretical Support Vector Machine Humans Neural Networks, Computer Artificial Intelligence Algorithms
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Computational determination of hERG-related cardiotoxicity of drug candidates.

BMC bioinformatics May 29, 2019
BACKGROUND: Drug candidates often cause an unwanted blockage of the potassium ion channel of the human ether-a-go-go-related gene (hERG). The blockage leads to long QT syndrome (LQTS), which is a severe life-threatening cardiac side effect. Therefore...
Databases, Genetic Area Under Curve Cardiotoxicity Neural Networks, Computer Humans Guinea Pigs Machine Learning Ether-A-Go-Go Potassium Channels Animals ROC Curve
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