AIMC Topic: Area Under Curve

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Drug Repositioning by Integrating Known Disease-Gene and Drug-Target Associations in a Semi-supervised Learning Model.

Acta biotheoretica Apr 26, 2018
Computational drug repositioning has been proven as a promising and efficient strategy for discovering new uses from existing drugs. To achieve this goal, a number of computational methods have been proposed, which are based on different data sources...
Drug Repositioning Area Under Curve Pharmaceutical Preparations Supervised Machine Learning Pharmacology Software Reproducibility of Results Computational Biology Models, Statistical Drug Therapy Pharmacy Humans
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Machine learning to predict the occurrence of bisphosphonate-related osteonecrosis of the jaw associated with dental extraction: A preliminary report.

Bone Apr 24, 2018
INTRODUCTION: The aim of this study was to build and validate five types of machine learning models that can predict the occurrence of BRONJ associated with dental extraction in patients taking bisphosphonates for the management of osteoporosis.
Female Aged Male ROC Curve Support Vector Machine Humans Neural Networks, Computer Machine Learning Decision Trees Area Under Curve Tooth Extraction Bisphosphonate-Associated Osteonecrosis of the Jaw
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Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization.

PloS one Apr 19, 2018
We aimed to evaluate a computer-aided diagnosis (CADx) system for lung nodule classification focussing on (i) usefulness of the conventional CADx system (hand-crafted imaging feature + machine learning algorithm), (ii) comparison between support vect...
Machine Learning Algorithms Databases, Factual Tomography, X-Ray Computed Diagnosis, Computer-Assisted Area Under Curve ROC Curve Humans Bayes Theorem Image Processing, Computer-Assisted Lung Neoplasms Support Vector Machine Solitary Pulmonary Nodule
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Using machine learning on cardiorespiratory fitness data for predicting hypertension: The Henry Ford ExercIse Testing (FIT) Project.

PloS one Apr 18, 2018
This study evaluates and compares the performance of different machine learning techniques on predicting the individuals at risk of developing hypertension, and who are likely to benefit most from interventions, using the cardiorespiratory fitness da...
Young Adult Adult Cardiorespiratory Fitness Male Machine Learning Middle Aged Humans Hypertension Adolescent Databases, Factual Neural Networks, Computer Support Vector Machine Female Area Under Curve Aged Bayes Theorem Aged, 80 and over Exercise Test
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Computer-aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI.

Journal of magnetic resonance imaging : JMRI Apr 16, 2018
BACKGROUND: Deep learning is the most promising methodology for automatic computer-aided diagnosis of prostate cancer (PCa) with multiparametric MRI (mp-MRI).
Diffusion Magnetic Resonance Imaging Reproducibility of Results Humans ROC Curve Neural Networks, Computer Sensitivity and Specificity Predictive Value of Tests Software Male Area Under Curve Databases, Factual Diagnosis, Computer-Assisted Prostatic Neoplasms Retrospective Studies Deep Learning Pattern Recognition, Automated
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Predicting Changes in Pediatric Medical Complexity using Large Longitudinal Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 16, 2018
Medically complex patients consume a disproportionate amount of care resources in hospitals but still often end up with sub-optimal clinical outcomes. Predicting dynamics of complexity in such patients can potentially help improve the quality of care...
Data Mining Humans Neural Networks, Computer Datasets as Topic Electronic Health Records Clinical Coding Logistic Models Child Child Health Services Longitudinal Studies ROC Curve Area Under Curve Patient Acuity
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Classifying Acute Ischemic Stroke Onset Time using Deep Imaging Features.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 16, 2018
Models have been developed to predict stroke outcomes (e.g., mortality) in attempt to provide better guidance for stroke treatment. However, there is little work in developing classification models for the problem of unknown time-since-stroke (TSS), ...
ROC Curve Area Under Curve Humans Aged Support Vector Machine Stroke Machine Learning Sensitivity and Specificity Prognosis Brain Ischemia Magnetic Resonance Imaging Male Female Regression Analysis Middle Aged Deep Learning
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Calibration Drift Among Regression and Machine Learning Models for Hospital Mortality.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 16, 2018
Advanced regression and machine learning models can provide personalized risk predictions to support clinical decision-making. We aimed to understand whether modeling methods impact the tendency of calibration to deteriorate as patient populations sh...
Hospital Mortality Logistic Models United States Models, Statistical Humans Calibration Area Under Curve Machine Learning Neural Networks, Computer Proportional Hazards Models Female United States Department of Veterans Affairs Adult Risk Male Hospitals, Veterans
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Automated detection of focal cortical dysplasia type II with surface-based magnetic resonance imaging postprocessing and machine learning.

Epilepsia Apr 10, 2018
OBJECTIVE: Focal cortical dysplasia (FCD) is a major pathology in patients undergoing surgical resection to treat pharmacoresistant epilepsy. Magnetic resonance imaging (MRI) postprocessing methods may provide essential help for detection of FCD. In ...
Female Young Adult Adult Sensitivity and Specificity Male Humans Machine Learning Brain Magnetic Resonance Imaging Middle Aged Area Under Curve Adolescent Epilepsy Child, Preschool Neuroimaging Child Malformations of Cortical Development, Group I ROC Curve
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Transfer Learning for Molecular Cancer Classification Using Deep Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics Apr 4, 2018
The emergence of deep learning has impacted numerous machine learning based applications and research. The reason for its success lies in two main advantages: 1) it provides the ability to learn very complex non-linear relationships between features ...
Deep Learning Genomics Computational Biology Models, Statistical Area Under Curve Linear Models Pattern Recognition, Automated Gene Expression Regulation Algorithms Neoplasms Gene Expression Profiling Transcriptome Diagnosis, Computer-Assisted Humans Neural Networks, Computer Software
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