AIMC Topic: Predictive Value of Tests

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Neural network-based model predictive tracking control of an uncertain robotic manipulator with input constraints.

ISA transactions Oct 8, 2020
This paper proposes a neural network-based model predictive control (MPC) method for robotic manipulators with model uncertainty and input constraints. In the presented NN-based MPC structure, two groups of radial basis function neural networks (RBFN...
Neural Networks, Computer Machine Learning Algorithms Computer Simulation Models, Theoretical Predictive Value of Tests Robotics Robotic Surgical Procedures Uncertainty
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A machine learning algorithm supports ultrasound-naïve novices in the acquisition of diagnostic echocardiography loops and provides accurate estimation of LVEF.

The international journal of cardiovascular imaging Oct 8, 2020
Left ventricular ejection fraction (LVEF) is the most important parameter in the assessment of cardiac function. A machine-learning algorithm was trained to guide ultrasound-novices to acquire diagnostic echocardiography images. The artificial intell...
Echocardiography Middle Aged Pilot Projects Clinical Competence Predictive Value of Tests Heart Diseases Image Interpretation, Computer-Assisted Aged Adult Students, Medical Male Ventricular Function, Left Stroke Volume Humans Machine Learning Female Reproducibility of Results
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Prospective Validation of Vesical Imaging-Reporting and Data System Using a Next-Generation Magnetic Resonance Imaging Scanner-Is Denoising Deep Learning Reconstruction Useful?

The Journal of urology Oct 6, 2020
PURPOSE: The Vesical Imaging Reporting and Data System (VI-RADS) was launched in 2018 to standardize reporting of magnetic resonance imaging for bladder cancer. This study aimed to prospectively validate VI-RADS using a next-generation magnetic reson...
Carcinoma, Transitional Cell Multiparametric Magnetic Resonance Imaging Male Deep Learning Urinary Bladder Neoplasms Predictive Value of Tests Noise Humans Research Design Prospective Studies Female Aged Aged, 80 and over
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Machine learning-based FDG PET-CT radiomics for outcome prediction in larynx and hypopharynx squamous cell carcinoma.

Clinical radiology Oct 6, 2020
AIM: To determine whether machine learning-based radiomic feature analysis of baseline integrated 2-[F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET) computed tomography (CT) predicts disease progression in patients with locally a...
Humans Hypopharynx Machine Learning Female Positron Emission Tomography Computed Tomography Aged Carcinoma, Squamous Cell Neoplasm Recurrence, Local Adult Radiopharmaceuticals Male Fluorodeoxyglucose F18 Middle Aged Chemoradiotherapy Predictive Value of Tests Laryngeal Neoplasms
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Developing a Machine Learning Algorithm for Identifying Abnormal Urothelial Cells: A Feasibility Study.

Acta cytologica Oct 6, 2020
INTRODUCTION: Urine cytology plays an important role in diagnosing urothelial carcinoma (UC). However, urine cytology interpretation is subjective and difficult. Morphogo (ALAB, Boston, MA, USA), equipped with automatic acquisition and scanning, opti...
Humans Neural Networks, Computer Machine Learning Female Cytodiagnosis Diagnosis, Computer-Assisted Reproducibility of Results Urologic Neoplasms Aged Image Interpretation, Computer-Assisted Predictive Value of Tests Aged, 80 and over Urine Prostatic Neoplasms Male Proof of Concept Study Carcinoma Middle Aged Urothelium Feasibility Studies
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The Clinical Application of the Deep Learning Technique for Predicting Trigger Origins in Patients With Paroxysmal Atrial Fibrillation With Catheter Ablation.

Circulation. Arrhythmia and electrophysiology Oct 6, 2020
BACKGROUND: Non-pulmonary vein (NPV) trigger has been reported as an important predictor of recurrence post-atrial fibrillation ablation. Elimination of NPV triggers can reduce the recurrence of postablation atrial fibrillation. Deep learning was app...
Recurrence Computed Tomography Angiography Phlebography Pulmonary Veins Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Atrial Fibrillation Heart Rate Catheter Ablation Reproducibility of Results Risk Factors Aged Adult Male Middle Aged Risk Assessment Deep Learning Time Factors Treatment Outcome Action Potentials Humans Retrospective Studies Female
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Clinical Predictive Models for COVID-19: Systematic Study.

Journal of medical Internet research Oct 6, 2020
BACKGROUND: COVID-19 is a rapidly emerging respiratory disease caused by SARS-CoV-2. Due to the rapid human-to-human transmission of SARS-CoV-2, many health care systems are at risk of exceeding their health care capacities, in particular in terms of...
Algorithms Retrospective Studies Intensive Care Units SARS-CoV-2 Hospitalization Sensitivity and Specificity Humans Coronavirus Infections Neural Networks, Computer COVID-19 Testing Machine Learning Public Health Informatics Brazil Pandemics Clinical Laboratory Techniques Betacoronavirus Respiration, Artificial COVID-19 Pneumonia, Viral ROC Curve Predictive Value of Tests Area Under Curve
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Risk stratification for mortality in cardiovascular disease survivors: A survival conditional inference tree analysis.

Nutrition, metabolism, and cardiovascular diseases : NMCD Oct 3, 2020
BACKGROUND AND AIMS: Efficient analysis strategies for complex network with cardiovascular disease (CVD) risk stratification remain lacking. We sought to identify an optimized model to study CVD prognosis using survival conditional inference tree (SC...
Proteinuria Health Status Indicators Time Factors Hyperglycemia Age Factors Predictive Value of Tests Cause of Death Machine Learning Aged Prognosis Humans Male Female Reproducibility of Results Cardiovascular Diseases Risk Factors Middle Aged Risk Assessment China
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Prediction of incident myocardial infarction using machine learning applied to harmonized electronic health record data.

BMC medical informatics and decision making Oct 2, 2020
BACKGROUND: With cardiovascular disease increasing, substantial research has focused on the development of prediction tools. We compare deep learning and machine learning models to a baseline logistic regression using only 'known' risk factors in pre...
Humans Machine Learning Myocardial Infarction Electronic Health Records Female Case-Control Studies Incidence Predictive Value of Tests
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Optimization of an automated tumor-infiltrating lymphocyte algorithm for improved prognostication in primary melanoma.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Oct 1, 2020
Tumor-infiltrating lymphocytes (TIL) have potential prognostic value in melanoma and have been considered for inclusion in the American Joint Committee on Cancer (AJCC) staging criteria. However, interobserver discordance continues to prevent the ado...
Humans Machine Learning Automation, Laboratory Databases, Factual Retrospective Studies Disease Progression Biopsy Aged Diagnosis, Computer-Assisted Female Neoplasm Recurrence, Local Lymphocytes, Tumor-Infiltrating Adult Progression-Free Survival Melanoma Predictive Value of Tests Tumor Microenvironment Microscopy Neoplasm Staging Skin Neoplasms Male Image Interpretation, Computer-Assisted Reproducibility of Results Middle Aged Lymphocyte Count Risk Factors Risk Assessment
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