AI Medical Compendium Topic:
Area Under Curve

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Deep-learning classification using convolutional neural network for evaluation of maxillary sinusitis on panoramic radiography.

Oral radiology Dec 11, 2018
OBJECTIVES: To apply a deep-learning system for diagnosis of maxillary sinusitis on panoramic radiography, and to clarify its diagnostic performance.
Deep Learning Area Under Curve Radiography, Panoramic Maxillary Sinusitis Humans Neural Networks, Computer
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Identifying disease genes using machine learning and gene functional similarities, assessed through Gene Ontology.

PloS one Dec 10, 2018
Identifying disease genes from a vast amount of genetic data is one of the most challenging tasks in the post-genomic era. Also, complex diseases present highly heterogeneous genotype, which difficult biological marker identification. Machine learnin...
Humans Machine Learning Phenotype Autism Spectrum Disorder User-Computer Interface Attention Deficit Disorder with Hyperactivity ROC Curve Area Under Curve Gene Ontology
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Deep Learning for Image Quality Assessment of Fundus Images in Retinopathy of Prematurity.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Accurate image-based medical diagnosis relies upon adequate image quality and clarity. This has important implications for clinical diagnosis, and for emerging methods such as telemedicine and computer-based image analysis. In this study, we trained ...
Humans Neural Networks, Computer Algorithms Area Under Curve Fundus Oculi Retina Telemedicine Infant, Newborn Reproducibility of Results Deep Learning ROC Curve Infant, Premature Retinopathy of Prematurity
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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...
ROC Curve Area Under Curve Peptic Ulcer Hemorrhage Neural Networks, Computer Algorithms Electronic Health Records Risk Assessment Humans
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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...
Radiography, Thoracic Middle Aged Diagnosis, Computer-Assisted Area Under Curve Length of Stay Supervised Machine Learning Risk Factors Humans Cohort Studies Unified Medical Language System Aged Electronic Health Records Respiratory Distress Syndrome Adult Female Predictive Value of Tests Male Natural Language Processing
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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...
Area Under Curve Supervised Machine Learning Humans Drug-Related Side Effects and Adverse Reactions Medical Informatics Algorithms Models, Statistical
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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...
Support Vector Machine Area Under Curve Models, Biological ROC Curve Logistic Models Body Mass Index Humans Reproducibility of Results Sensitivity and Specificity 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.
Humans Machine Learning Forecasting Retrospective Studies ROC Curve Logistic Models Triage Area Under Curve Emergency Service, Hospital Bayes Theorem Patient Admission Adult New South Wales Male Female Middle Aged Aged Adolescent Aged, 80 and over
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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...
Diagnosis, Computer-Assisted Deep Learning Models, Theoretical Area Under Curve Middle Aged Disease Progression Severity of Illness Index Diagnostic Techniques, Ophthalmological Photography Retinal Drusen Geographic Atrophy Prospective Studies Female Reproducibility of Results Risk Factors Aged Aged, 80 and over Sensitivity and Specificity Male Humans
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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...
Databases, Protein Area Under Curve Protein Domains Molecular Sequence Annotation Amino Acid Sequence Gene Ontology Algorithms Computational Biology Proteins
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