AIMC Topic: ROC Curve

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A Computer-Aided Diagnosis System Using Artificial Intelligence for the Diagnosis and Characterization of Thyroid Nodules on Ultrasound: Initial Clinical Assessment.

Thyroid : official journal of the American Thyroid Association Feb 28, 2017
BACKGROUND: An initial clinical assessment is described of a new, commercially available, computer-aided diagnosis (CAD) system using artificial intelligence (AI) for thyroid ultrasound, and its performance is evaluated in the diagnosis of malignant ...
Male Middle Aged Diagnosis, Computer-Assisted Thyroid Diseases Female Aged Adult Sensitivity and Specificity Humans Area Under Curve Artificial Intelligence Biopsy, Fine-Needle Carcinoma, Papillary Biopsy, Large-Core Needle Thyroid Cancer, Papillary Thyroid Neoplasms Ultrasonography Thyroid Nodule ROC Curve
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A novel hierarchical selective ensemble classifier with bioinformatics application.

Artificial intelligence in medicine Feb 27, 2017
Selective ensemble learning is a technique that selects a subset of diverse and accurate basic models in order to generate stronger generalization ability. In this paper, we proposed a novel learning algorithm that is based on parallel optimization a...
Protein Interaction Maps Computational Biology Databases, Genetic Proteins Machine Learning Reproducibility of Results ROC Curve Area Under Curve Data Mining RNA, Transfer
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Prediction of Prolonged Ventilation after Coronary Artery Bypass Grafting: Data from an Artificial Neural Network.

The heart surgery forum Feb 24, 2017
OBJECTIVES: The need for mechanical ventilation 24 hours after coronary artery bypass grafting (CABG) is considered a morbidity by the Society of Thoracic Surgeons. The purpose of this investigation was twofold: to identify simple preoperative patien...
Coronary Artery Bypass Aged Male Middle Aged Postoperative Complications Respiration, Artificial ROC Curve Coronary Artery Disease Odds Ratio Prognosis Retrospective Studies Female Risk Factors Humans Neural Networks, Computer
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Feature Extraction and Classification of EHG between Pregnancy and Labour Group Using Hilbert-Huang Transform and Extreme Learning Machine.

Computational and mathematical methods in medicine Feb 19, 2017
Preterm birth (PTB) is the leading cause of perinatal mortality and long-term morbidity, which results in significant health and economic problems. The early detection of PTB has great significance for its prevention. The electrohysterogram (EHG) rel...
Medical Informatics Electronic Data Processing Labor, Obstetric Uterine Contraction Monitoring, Physiologic Humans Models, Statistical Machine Learning Bayes Theorem Algorithms Signal Processing, Computer-Assisted Pregnancy Databases, Factual Female Reproducibility of Results ROC Curve
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Predicting antimicrobial peptides with improved accuracy by incorporating the compositional, physico-chemical and structural features into Chou's general PseAAC.

Scientific reports Feb 13, 2017
Antimicrobial peptides (AMPs) are important components of the innate immune system that have been found to be effective against disease causing pathogens. Identification of AMPs through wet-lab experiment is expensive. Therefore, development of effic...
Antiviral Agents Support Vector Machine Databases, Protein Antimicrobial Cationic Peptides ROC Curve Area Under Curve Antifungal Agents Chemical Phenomena
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A case-based reasoning system based on weighted heterogeneous value distance metric for breast cancer diagnosis.

Artificial intelligence in medicine Feb 11, 2017
OBJECTIVE: We present the implementation and application of a case-based reasoning (CBR) system for breast cancer related diagnoses. By retrieving similar cases in a breast cancer decision support system, oncologists can obtain powerful information o...
Humans Software Algorithms Decision Support Techniques Female Breast Neoplasms ROC Curve Expert Systems
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Classification-by-Analogy: Using Vector Representations of Implicit Relationships to Identify Plausibly Causal Drug/Side-effect Relationships.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
An important aspect of post-marketing drug surveillance involves identifying potential side-effects utilizing adverse drug event (ADE) reporting systems and/or Electronic Health Records. These data are noisy, necessitating identified drug/ADE associa...
Product Surveillance, Postmarketing Models, Theoretical Humans Support Vector Machine Machine Learning Drug-Related Side Effects and Adverse Reactions Electronic Health Records Adverse Drug Reaction Reporting Systems ROC Curve
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Controlling testing volume for respiratory viruses using machine learning and text mining.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 10, 2017
Viral testing for pediatric inpatients with respiratory symptoms is common, with considerable associated charges. In an attempt to reduce testing volumes, we studied whether data available at the time of admission could aid in identifying children wi...
Humans Electronic Health Records Child Machine Learning ROC Curve Male Female Data Mining Models, Theoretical Retrospective Studies Infant Hospitalization Respiratory Tract Infections Decision Trees Adolescent Sensitivity and Specificity Virus Diseases Child, Preschool Viruses
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Structured Pyramidal Neural Networks.

International journal of neural systems Feb 9, 2017
The Pyramidal Neural Networks (PNN) are an example of a successful recently proposed model inspired by the human visual system and deep learning theory. PNNs are applied to computer vision and based on the concept of receptive fields. This paper prop...
Pyramidal Cells Visual Pathways Time Factors ROC Curve Image Processing, Computer-Assisted Humans Support Vector Machine Neural Networks, Computer Models, Neurological Female Area Under Curve Male Pattern Recognition, Automated Blood Cells
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Gradient Boosted Decision Tree Classification of Endophthalmitis Versus Uveitis and Lymphoma from Aqueous and Vitreous IL-6 and IL-10 Levels.

Journal of ocular pharmacology and therapeutics : the official journal of the Association for Ocular Pharmacology and Therapeutics Feb 3, 2017
PURPOSE: To investigate the effectiveness of gradient boosting to classify endophthalmitis versus uveitis and lymphoma by intraocular cytokine levels.
ROC Curve Lymphoma Decision Trees Data Interpretation, Statistical Uveitis Humans Machine Learning Endophthalmitis Interleukin-10 Interleukin-6 Water
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