AIMC Topic: Predictive Value of Tests

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Automated Detection of Vulnerable Plaque for Intravascular Optical Coherence Tomography Images.

Cardiovascular engineering and technology Sep 18, 2019
PURPOSE: Vulnerable plaque detection is important to acute coronary syndrome (ACS) diagnosis. In recent years, intravascular optical coherence tomography (IVOCT) imaging has been used for vulnerable plaque detection. Current automated detection metho...
Automation Coronary Vessels Rupture, Spontaneous Plaque, Atherosclerotic Diagnosis, Computer-Assisted Predictive Value of Tests Tomography, Optical Coherence Coronary Artery Disease Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Prognosis Reproducibility of Results
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Machine Learning to Predict the Risk of Incident Heart Failure Hospitalization Among Patients With Diabetes: The WATCH-DM Risk Score.

Diabetes care Sep 13, 2019
OBJECTIVE: To develop and validate a novel, machine learning-derived model to predict the risk of heart failure (HF) among patients with type 2 diabetes mellitus (T2DM).
Outpatients Follow-Up Studies Predictive Value of Tests Heart Failure Clinical Trials as Topic Hospitalization Aged Male Middle Aged Cohort Studies Humans Time Factors Female Machine Learning Diabetes Mellitus, Type 2 Reproducibility of Results Risk Assessment Incidence Risk Factors
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Artificial intelligence-based versus manual assessment of prostate cancer in the prostate gland: a method comparison study.

Clinical physiology and functional imaging Sep 8, 2019
AIM: To test the feasibility of a fully automated artificial intelligence-based method providing PET measures of prostate cancer (PCa).
Automation Fluorine Radioisotopes Prostatectomy Feasibility Studies Radiopharmaceuticals Choline Image Interpretation, Computer-Assisted Neural Networks, Computer Aged Male Middle Aged Prostatic Neoplasms Humans Prostate Predictive Value of Tests Workflow Positron Emission Tomography Computed Tomography
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Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery.

Circulation. Cardiovascular quality and outcomes Sep 5, 2019
BACKGROUND: The ECG remains the most widely used diagnostic test for characterization of cardiac structure and electrical activity. We hypothesized that parallel advances in computing power, machine learning algorithms, and availability of large-scal...
Prognosis Reproducibility of Results Cardiovascular Diseases Diagnosis, Computer-Assisted Action Potentials Predictive Value of Tests Signal Processing, Computer-Assisted Time Factors Electrocardiography Humans Neural Networks, Computer Machine Learning Databases, Factual Workflow Heart Rate Markov Chains Pattern Recognition, Automated
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A Machine Learning-Based QSAR Model for Benzimidazole Derivatives as Corrosion Inhibitors by Incorporating Comprehensive Feature Selection.

Interdisciplinary sciences, computational life sciences Sep 4, 2019
BACKGROUND: Computational prediction of inhibition efficiency (IE) for inhibitor molecules is a crucial supplementary way to design novel molecules that can efficiently inhibit corrosion onto metallic surfaces.
Computational Biology Support Vector Machine Cluster Analysis Predictive Value of Tests Hydrazines Machine Learning Algorithms Metals Imaging, Three-Dimensional Benzimidazoles Linear Models Chemistry Corrosion Conservation of Natural Resources Quantitative Structure-Activity Relationship Static Electricity
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Prevalence and Predictability of Low-Yield Inpatient Laboratory Diagnostic Tests.

JAMA network open Sep 4, 2019
IMPORTANCE: Laboratory testing is an important target for high-value care initiatives, constituting the highest volume of medical procedures. Prior studies have found that up to half of all inpatient laboratory tests may be medically unnecessary, but...
L-Lactate Dehydrogenase Blood Urea Nitrogen Leukocyte Count Clinical Laboratory Techniques Area Under Curve Glycated Hemoglobin Hemoglobins Troponin I Female Hospitalization Aged Adult Middle Aged ROC Curve Predictive Value of Tests Sensitivity and Specificity Male Humans Machine Learning Retrospective Studies
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Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association.

The Journal of pathology Sep 3, 2019
In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated pa...
Humans Artificial Intelligence Image Interpretation, Computer-Assisted Terminology as Topic Computer Security Diagnosis, Computer-Assisted Pathology Predictive Value of Tests Policy Making Workflow Benchmarking
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Machine learning based prediction of perioperative blood loss in orthognathic surgery.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery Aug 30, 2019
The aim of this study was to evaluate, if and with what accuracy perioperative blood loss can be calculated by a machine learning algorithm prior to orthognathic surgery. The investigators implemented a random forest algorithm to predict perioperativ...
Predictive Value of Tests Humans Orthognathic Surgical Procedures Machine Learning Orthopedic Procedures Treatment Outcome Orthognathic Surgery Blood Loss, Surgical
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Machine learning in predicting graft failure following kidney transplantation: A systematic review of published predictive models.

International journal of medical informatics Aug 24, 2019
INTRODUCTION: Machine learning has been increasingly used to develop predictive models to diagnose different disease conditions. The heterogeneity of the kidney transplant population makes predicting graft outcomes extremely challenging. Several kidn...
Humans Neural Networks, Computer Machine Learning Kidney Transplantation Predictive Value of Tests Databases, Factual Decision Trees Graft Rejection Bayes Theorem
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SVR ensemble-based continuous blood pressure prediction using multi-channel photoplethysmogram.

Computers in biology and medicine Aug 19, 2019
In this paper, a continuous non-occluding blood pressure (BP) prediction method is proposed using multiple photoplethysmogram (PPG) signals. In the new method, BP is predicted by a committee machine or ensemble learning framework comprising multiple ...
Predictive Value of Tests Blood Pressure Pulse Wave Analysis Signal Processing, Computer-Assisted Humans Photoplethysmography Blood Pressure Determination Support Vector Machine
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