AIMC Topic: Area Under 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...
Algorithms Electronic Health Records Humans Area Under Curve Risk Assessment Neural Networks, Computer Peptic Ulcer Hemorrhage ROC Curve
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A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Acute Respiratory Distress Syndrome (ARDS) is a syndrome of respiratory failure that may be identified using text from radiology reports. The objective of this study was to determine whether natural language processing (NLP) with machine learning per...
Diagnosis, Computer-Assisted Unified Medical Language System Aged Radiography, Thoracic Length of Stay Predictive Value of Tests Adult Cohort Studies Male Natural Language Processing Respiratory Distress Syndrome Middle Aged Humans Area Under Curve Electronic Health Records Supervised Machine Learning Female Risk Factors
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Identification of Drug-Side Effect Association via Semisupervised Model and Multiple Kernel Learning.

IEEE journal of biomedical and health informatics Nov 28, 2018
Drug-side effect association contains the information on marketed medicines and their recorded adverse drug reactions. Traditional experimental method is time consuming and expensive. All associations of drugs and side-effects are seen as a bipartite...
Models, Statistical Humans Supervised Machine Learning Algorithms Area Under Curve Drug-Related Side Effects and Adverse Reactions Medical Informatics
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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...
Area Under Curve Models, Biological ROC Curve Humans Logistic Models Reproducibility of Results Body Mass Index Sensitivity and Specificity Support Vector Machine Colorectal Neoplasms
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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.
Logistic Models Triage Area Under Curve Emergency Service, Hospital Male New South Wales Machine Learning Middle Aged Bayes Theorem Forecasting Adolescent Patient Admission Female Retrospective Studies ROC Curve Aged Humans Aged, 80 and over Adult
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DeepSeeNet: A Deep Learning Model for Automated Classification of Patient-based Age-related Macular Degeneration Severity from Color Fundus Photographs.

Ophthalmology Nov 22, 2018
PURPOSE: In assessing the severity of age-related macular degeneration (AMD), the Age-Related Eye Disease Study (AREDS) Simplified Severity Scale predicts the risk of progression to late AMD. However, its manual use requires the time-consuming partic...
Humans Prospective Studies Risk Factors Aged Aged, 80 and over Female Area Under Curve Reproducibility of Results Severity of Illness Index Diagnostic Techniques, Ophthalmological Sensitivity and Specificity Photography Diagnosis, Computer-Assisted Male Retinal Drusen Middle Aged Deep Learning Disease Progression Models, Theoretical Geographic Atrophy
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Computational discovery of direct associations between GO terms and protein domains.

BMC bioinformatics Nov 20, 2018
BACKGROUND: Families of related proteins and their different functions may be described systematically using common classifications and ontologies such as Pfam and GO (Gene Ontology), for example. However, many proteins consist of multiple domains, a...
Amino Acid Sequence Molecular Sequence Annotation Gene Ontology Proteins Databases, Protein Area Under Curve Protein Domains Algorithms Computational Biology
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Development of an artificial intelligence system to classify pathology and clinical features on retinal fundus images.

Clinical & experimental ophthalmology Nov 15, 2018
IMPORTANCE: Artificial intelligence (AI) algorithms are under development for use in diabetic retinopathy photo screening pathways. To be clinically acceptable, such systems must also be able to classify other fundus abnormalities and clinical featur...
Glaucoma Artificial Intelligence Databases, Factual Retrospective Studies Humans Diabetic Retinopathy Fundus Oculi Retina Macular Edema Macular Degeneration Photography Reproducibility of Results Sensitivity and Specificity ROC Curve Area Under Curve
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Prediction of Farnesoid X Receptor Disruptors with Machine Learning Methods.

Chemical research in toxicology Nov 8, 2018
The farnesoid X receptor (FXR) emerges as a promising drug target involved in regulating various metabolic pathways, yet some xenobiotic compounds binding to FXR would be an important determinant to induce the receptor dysfunctions that lead to undes...
Receptors, Cytoplasmic and Nuclear Xenobiotics ROC Curve Machine Learning Humans Area Under Curve Databases, Factual Benzimidazoles
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Predominant polarity classification and associated clinical variables in bipolar disorder: A machine learning approach.

Journal of affective disorders Nov 6, 2018
BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder characterized by periodic episodes of manic and depressive symptomatology. Predominant polarity (PP) appears to be an important specifier of BD. The present study employed machine lea...
Humans Adult Cross-Sectional Studies Male Middle Aged Bipolar Disorder Machine Learning Algorithms Female Hospitalization Feeding and Eating Disorders Hallucinations Delusions Area Under Curve Alcoholism Tobacco Use Disorder Demography Cohort Studies ROC Curve Age Factors Substance-Related Disorders
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