AIMC Topic: Predictive Value of Tests

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Prediction of molecular subtypes of breast cancer using BI-RADS features based on a "white box" machine learning approach in a multi-modal imaging setting.

European journal of radiology Mar 21, 2019
PURPOSE: To develop and validate an interpretable and repeatable machine learning model approach to predict molecular subtypes of breast cancer from clinical metainformation together with mammography and MRI images.
Multimodal Imaging Predictive Value of Tests Neoplasm Staging Humans Machine Learning Retrospective Studies Female Adult Breast Neoplasms Middle Aged Gene Expression Regulation, Neoplastic
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Machine Learning Using CT-FFR Predicts Proximal Atherosclerotic Plaque Formation Associated With LAD Myocardial Bridging.

JACC. Cardiovascular imaging Mar 13, 2019
Fractional Flow Reserve, Myocardial Myocardial Bridging Male Middle Aged Time Factors Predictive Value of Tests Coronary Angiography Coronary Artery Disease Image Interpretation, Computer-Assisted Coronary Vessels Plaque, Atherosclerotic Computed Tomography Angiography Prognosis Retrospective Studies Female Risk Factors Aged Humans Machine Learning
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Prospective validation of a deep learning electrocardiogram algorithm for the detection of left ventricular systolic dysfunction.

Journal of cardiovascular electrophysiology Mar 10, 2019
OBJECTIVES: We sought to validate a deep learning algorithm designed to predict an ejection fraction (EF) less than or equal to 35% based on the 12-lead electrocardiogram (ECG) in a large prospective cohort.
Reproducibility of Results Aged Aged, 80 and over Male Ventricular Function, Left Humans Electrocardiography Prospective Studies Stroke Volume Predictive Value of Tests Prognosis Echocardiography Female Signal Processing, Computer-Assisted Middle Aged Heart Rate Diagnosis, Computer-Assisted Ventricular Dysfunction, Left Deep Learning
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Identification of esophageal cancer pathway deviation and construction of a diagnosis model using three kernel genes.

Journal of cellular physiology Mar 5, 2019
The purpose of this study is to better understand the role of interleukin 35 (IL35) in esophageal carcinoma by comparing the mRNA level in Barrett's esophageal mucosa and in matched normal squamous mucosa and to understand how the diagnosis model wor...
Gene Expression Profiling Transcriptome Case-Control Studies Deep Learning Gene Expression Regulation, Neoplastic Humans Reproducibility of Results Biomarkers, Tumor Esophageal Neoplasms Cyclic AMP Response Element-Binding Protein Esophageal Squamous Cell Carcinoma Hepatocyte Nuclear Factor 1-beta Interleukin-12 Subunit p35 Models, Genetic Databases, Genetic Early Detection of Cancer Nerve Tissue Proteins Predictive Value of Tests
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Natural Language Processing of Radiology Reports in Patients With Hepatocellular Carcinoma to Predict Radiology Resource Utilization.

Journal of the American College of Radiology : JACR Mar 2, 2019
OBJECTIVE: Radiology is a finite health care resource in high demand at most health centers. However, anticipating fluctuations in demand is a challenge because of the inherent uncertainty in disease prognosis. The aim of this study was to explore th...
Radiology Department, Hospital Health Resources ROC Curve Female Humans Predictive Value of Tests Aged Machine Learning Liver Neoplasms Natural Language Processing Sensitivity and Specificity Databases, Factual Carcinoma, Hepatocellular Area Under Curve Male Retrospective Studies Ontario Research Report Middle Aged Tomography, X-Ray Computed Radiology Information Systems
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Model-based hearing diagnostics based on wideband tympanometry measurements utilizing fuzzy arithmetic.

Hearing research Feb 28, 2019
Today's audiometric methods for the diagnosis of middle ear disease are often based on a comparison of measurements with standard curves, that represent the statistical range of normal hearing responses. Because of large inter-individual variances in...
Hearing Joints Ligaments Tympanic Membrane Ear, Middle Reproducibility of Results Models, Theoretical Fuzzy Logic Humans Cluster Analysis Ear Diseases Predictive Value of Tests Ear Canal Acoustic Impedance Tests Ear Ossicles
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Identifying Ventricular Arrhythmias and Their Predictors by Applying Machine Learning Methods to Electronic Health Records in Patients With Hypertrophic Cardiomyopathy (HCM-VAr-Risk Model).

The American journal of cardiology Feb 27, 2019
Clinical risk stratification for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HC) employs rules derived from American College of Cardiology Foundation/American Heart Association (ACCF/AHA) guidelines or the HCM Risk-SCD model (C-index ∼...
Middle Aged Electronic Health Records Humans Risk Assessment Cardiomyopathy, Hypertrophic Female Machine Learning Electrocardiography Reproducibility of Results Prognosis Tachycardia, Ventricular Predictive Value of Tests Retrospective Studies Risk Factors Echocardiography, Stress Registries Male Magnetic Resonance Imaging, Cine
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Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge.

Medical image analysis Feb 27, 2019
Tumor proliferation is an important biomarker indicative of the prognosis of breast cancer patients. Assessment of tumor proliferation in a clinical setting is a highly subjective and labor-intensive task. Previous efforts to automate tumor prolifera...
Pathology Image Processing, Computer-Assisted Cell Proliferation Predictive Value of Tests Prognosis Gene Expression Female Mitosis Breast Neoplasms Biomarkers, Tumor Humans Deep Learning
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A novel machine-learning-based infection screening system via 2013-2017 seasonal influenza patients' vital signs as training datasets.

The Journal of infection Feb 22, 2019
Aged, 80 and over Young Adult Adult Sensitivity and Specificity Male Middle Aged Adolescent Child Mass Screening Predictive Value of Tests Humans Machine Learning Female Aged Influenza, Human Vital Signs Clinical Decision Rules
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The Early Psychosis Screener for Internet (EPSI)-SR: Predicting 12 month psychotic conversion using machine learning.

Schizophrenia research Feb 15, 2019
INTRODUCTION: A faster and more accurate self-report screener for early psychosis is needed to promote early identification and intervention.
Psychotic Disorders Early Diagnosis Risk Assessment Diagnosis, Computer-Assisted Humans Support Vector Machine Machine Learning Predictive Value of Tests Internet
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