AIMC Topic:
ROC Curve

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A Hybrid Residual Network and Long Short-Term Memory Method for Peptic Ulcer Bleeding Mortality Prediction.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
The prediction of patient mortality, which can detect high-risk patients, is a significant yet challenging problem in medical informatics. Thanks to the wide adoption of electronic health records (EHRs), many data-driven methods have been proposed to...
Peptic Ulcer Hemorrhage Electronic Health Records Humans Risk Assessment Neural Networks, Computer Algorithms ROC Curve Area Under Curve
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Machine-learned models using hematological inflammation markers in the prediction of short-term acute coronary syndrome outcomes.

Journal of translational medicine Dec 3, 2018
BACKGROUND: Increased systemic and local inflammation play a vital role in the pathophysiology of acute coronary syndrome. This study aimed to assess the usefulness of selected machine learning methods and hematological markers of inflammation in pre...
Machine Learning Biomarkers Reproducibility of Results Aged Humans Inflammation Models, Theoretical Treatment Outcome Acute Coronary Syndrome Time Factors Hospital Mortality ROC Curve Logistic Models
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Predicting response to somatostatin analogues in acromegaly: machine learning-based high-dimensional quantitative texture analysis on T2-weighted MRI.

European radiology Nov 30, 2018
OBJECTIVE: To investigate the value of machine learning (ML)-based high-dimensional quantitative texture analysis (qTA) on T2-weighted magnetic resonance imaging (MRI) in predicting response to somatostatin analogues (SA) in acromegaly patients with ...
Acromegaly Somatostatin Pituitary Neoplasms Adenoma Humans Male Predictive Value of Tests Machine Learning Middle Aged Algorithms Female ROC Curve Retrospective Studies Magnetic Resonance Imaging Reproducibility of Results Young Adult Adult
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A comparison of logistic regression models with alternative machine learning methods to predict the risk of in-hospital mortality in emergency medical admissions via external validation.

Health informatics journal Nov 29, 2018
We compare the performance of logistic regression with several alternative machine learning methods to estimate the risk of death for patients following an emergency admission to hospital based on the patients' first blood test results and physiologi...
Hospitalization Hospital Mortality ROC Curve Humans Logistic Models Emergency Service, Hospital Machine Learning Patient Admission
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A Machine Learning Approach to Predicting Need for Hospitalization for Pediatric Asthma Exacerbation at the Time of Emergency Department Triage.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine Nov 29, 2018
OBJECTIVES: Pediatric asthma is a leading cause of emergency department (ED) utilization and hospitalization. Earlier identification of need for hospital-level care could triage patients more efficiently to high- or low-resource ED tracks. Existing t...
Triage Hospitalization Emergency Service, Hospital Humans Status Asthmaticus Male Machine Learning Child, Preschool Risk Assessment Retrospective Studies Child Adolescent Female ROC Curve Logistic Models
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A deep learning model for the detection of both advanced and early glaucoma using fundus photography.

PloS one Nov 27, 2018
PURPOSE: To build a deep learning model to diagnose glaucoma using fundus photography.
Humans Fundus Oculi Disease Progression Image Interpretation, Computer-Assisted Glaucoma Diagnostic Techniques, Ophthalmological Deep Learning Cross-Sectional Studies ROC Curve Logistic Models
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A reliable method for colorectal cancer prediction based on feature selection and support vector machine.

Medical & biological engineering & computing Nov 26, 2018
Colorectal cancer (CRC) is a common cancer responsible for approximately 600,000 deaths per year worldwide. Thus, it is very important to find the related factors and detect the cancer accurately. However, timely and accurate prediction of the diseas...
Humans Reproducibility of Results Body Mass Index Sensitivity and Specificity Support Vector Machine Area Under Curve Colorectal Neoplasms Models, Biological ROC Curve Logistic Models
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The Sydney Triage to Admission Risk Tool (START2) using machine learning techniques to support disposition decision-making.

Emergency medicine Australasia : EMA Nov 23, 2018
OBJECTIVE: To further develop and refine an Emergency Department (ED) in-patient admission prediction model using machine learning techniques.
Bayes Theorem Patient Admission New South Wales Logistic Models Triage Area Under Curve Emergency Service, Hospital Female Aged Aged, 80 and over Adult Male Middle Aged Adolescent ROC Curve Humans Machine Learning Forecasting Retrospective Studies
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Dual Convolutional Neural Network Based Method for Predicting Disease-Related miRNAs.

International journal of molecular sciences Nov 23, 2018
Identification of disease-related microRNAs (disease miRNAs) is helpful for understanding and exploring the etiology and pathogenesis of diseases. Most of recent methods predict disease miRNAs by integrating the similarities and associations of miRNA...
Databases, Genetic MicroRNAs Disease Susceptibility Humans Neural Networks, Computer Algorithms Reproducibility of Results ROC Curve Gene Regulatory Networks Genetic Predisposition to Disease Genetic Association Studies
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Detection of Breast Cancer with Mammography: Effect of an Artificial Intelligence Support System.

Radiology Nov 20, 2018
Purpose To compare breast cancer detection performance of radiologists reading mammographic examinations unaided versus supported by an artificial intelligence (AI) system. Materials and Methods An enriched retrospective, fully crossed, multireader, ...
Humans Adult Breast Neoplasms Middle Aged ROC Curve Artificial Intelligence Female Aged Aged, 80 and over Mammography Breast Radiographic Image Enhancement
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