AIMC Topic: Predictive Value of Tests

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Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients.

Investigative radiology Feb 1, 2019
PURPOSE: The aim of this study was to assess the potential of machine learning with multiparametric magnetic resonance imaging (mpMRI) for the early prediction of pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) and of survival ...
Reproducibility of Results Aged Adult Breast Neoplasms Middle Aged Humans Machine Learning Predictive Value of Tests Prospective Studies Breast Female Survival Analysis Chemotherapy, Adjuvant Diffusion Magnetic Resonance Imaging ROC Curve Treatment Outcome Neoadjuvant Therapy Magnetic Resonance Imaging
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Using Elastic Net Penalized Cox Proportional Hazards Regression to Identify Predictors of Imminent Smoking Lapse.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco Jan 4, 2019
INTRODUCTION: Machine learning algorithms such as elastic net regression and backward selection provide a unique and powerful approach to model building given a set of psychosocial predictors of smoking lapse measured repeatedly via ecological moment...
Humans Machine Learning Female Follow-Up Studies Predictive Value of Tests Proportional Hazards Models Smokers Recurrence Adult Male Middle Aged Smartphone Smoking Cessation Ecological Momentary Assessment Tobacco Smoking
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An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis.

Investigative ophthalmology & visual science Jan 2, 2019
PURPOSE: To detect visual field (VF) progression by analyzing spatial pattern changes.
False Positive Reactions Spatial Processing Vision Disorders Predictive Value of Tests Visual Fields Visual Field Tests Humans Glaucoma Artificial Intelligence Disease Progression Diagnosis, Computer-Assisted Cohort Studies Follow-Up Studies
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Optimizing Machine Learning Methods to Improve Predictive Models of Alzheimer's Disease.

Journal of Alzheimer's disease : JAD Jan 1, 2019
BACKGROUND: Predicting clinical course of cognitive decline can boost clinical trials' power and improve our clinical decision-making. Machine learning (ML) algorithms are specifically designed for the purpose of prediction; however. identifying opti...
Hippocampus Cerebral Cortex Apolipoproteins E Demography Middle Aged Cognitive Dysfunction Prognosis Support Vector Machine Female Humans Longitudinal Studies Magnetic Resonance Imaging Aged Machine Learning Models, Neurological Aged, 80 and over Predictive Value of Tests Male Discriminant Analysis Alzheimer Disease
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Fuzzy Classification Methods Based Diagnosis of Parkinson's disease from Speech Test Cases.

Current aging science Jan 1, 2019
BACKGROUND: Together with the Alzheimer's disease, Parkinson's disease is considered as one of the two serious known neurodegenerative diseases. Physicians find it hard to predict whether a given patient has already developed or is expected to develo...
Parkinson Disease Predictive Value of Tests Humans Machine Learning Speech Fuzzy Logic
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Accurate Identification of Colonoscopy Quality and Polyp Findings Using Natural Language Processing.

Journal of clinical gastroenterology Jan 1, 2019
OBJECTIVES: The aim of this study was to test the ability of a commercially available natural language processing (NLP) tool to accurately extract examination quality-related and large polyp information from colonoscopy reports with varying report fo...
Sensitivity and Specificity Female Humans Colonoscopy Reproducibility of Results Cross-Sectional Studies Predictive Value of Tests Aged Male Natural Language Processing Middle Aged Aged, 80 and over Colonic Polyps California
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Serum Aldosterone as Predictor of Progression of Coronary Heart Disease in Patients Without Signs of Heart Failure After Acute Myocardial Infarction.

Medical archives (Sarajevo, Bosnia and Herzegovina) Dec 1, 2018
INTRODUCTION: In patients with acute myocardial infarction (AMI) early risk assessment of development of complications is of great importance. It is proven that aldosterone level has a major role in progression of cardiovascular pathology.
Disease Progression Follow-Up Studies Predictive Value of Tests Myocardial Infarction Aldosterone Aged Humans Coronary Disease Male Biomarkers Middle Aged Prognosis Risk Assessment Female
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Impact of Deep Learning Assistance on the Histopathologic Review of Lymph Nodes for Metastatic Breast Cancer.

The American journal of surgical pathology Dec 1, 2018
Advances in the quality of whole-slide images have set the stage for the clinical use of digital images in anatomic pathology. Along with advances in computer image analysis, this raises the possibility for computer-assisted diagnostics in pathology ...
Pattern Recognition, Automated Proof of Concept Study Pathology, Clinical Biopsy Neoplasm Micrometastasis Workflow Female Image Interpretation, Computer-Assisted Reproducibility of Results Observer Variation Breast Neoplasms Time Factors Diagnosis, Computer-Assisted Lymph Nodes Deep Learning Lymphatic Metastasis Humans Predictive Value of Tests
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How Should Artificial Intelligence Screen for Skin Cancer and Deliver Diagnostic Predictions to Patients?

JAMA dermatology Dec 1, 2018
Humans Artificial Intelligence Skin Neoplasms Early Detection of Cancer Diagnostic Imaging Predictive Value of Tests Neoplasm Staging
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Support vector machine-based assessment of the T-wave morphology improves long QT syndrome diagnosis.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology Nov 1, 2018
AIMS: Diagnosing long QT syndrome (LQTS) is challenging due to a considerable overlap of the QTc-interval between LQTS patients and healthy controls. The aim of this study was to investigate the added value of T-wave morphology markers obtained from ...
Electrocardiography Support Vector Machine Action Potentials Predictive Value of Tests Long QT Syndrome Reproducibility of Results Signal Processing, Computer-Assisted Humans Heart Conduction System Risk Factors Heart Rate Phenotype Time Factors Retrospective Studies Genetic Predisposition to Disease
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