AIMC Topic:
Predictive Value of Tests

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Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence.

Archives of toxicology Apr 28, 2018
Human lungs are susceptible to the toxicity induced by soluble xenobiotics. However, the direct cellular effects of many pulmonotoxic chemicals are not always clear, and thus, a general in vitro assay for testing pulmonotoxicity applicable to a wide ...
Toxicity Tests Bronchi Xenobiotics Cell Line Cell Survival Predictive Value of Tests A549 Cells High-Throughput Screening Assays Humans Artificial Intelligence Sensitivity and Specificity Lung
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Natural Language Processing Accurately Calculates Adenoma and Sessile Serrated Polyp Detection Rates.

Digestive diseases and sciences Apr 26, 2018
BACKGROUND: ADR is a widely used colonoscopy quality indicator. Calculation of ADR is labor-intensive and cumbersome using current electronic medical databases. Natural language processing (NLP) is a method used to extract meaning from unstructured o...
Humans Electronic Health Records Quality Indicators, Health Care Female Automation Early Detection of Cancer Adenomatous Polyps Predictive Value of Tests Reproducibility of Results Natural Language Processing Male Colonic Neoplasms Colonoscopy Colonic Polyps Adenocarcinoma
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MuDeRN: Multi-category classification of breast histopathological image using deep residual networks.

Artificial intelligence in medicine Apr 26, 2018
MOTIVATION: Identifying carcinoma subtype can help to select appropriate treatment options and determining the subtype of benign lesions can be beneficial to estimate the patients' risk of developing cancer in the future. Pathologists' assessment of ...
Predictive Value of Tests Biopsy Coloring Agents Microscopy Image Interpretation, Computer-Assisted Pattern Recognition, Automated Eosine Yellowish-(YS) Hematoxylin Female Reproducibility of Results Breast Neoplasms Deep Learning Staining and Labeling Humans Databases, Factual
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Segmentation of corneal endothelium images using a U-Net-based convolutional neural network.

Artificial intelligence in medicine Apr 19, 2018
Diagnostic information regarding the health status of the corneal endothelium may be obtained by analyzing the size and the shape of the endothelial cells in specular microscopy images. Prior to the analysis, the endothelial cells need to be extracte...
Cell Shape Cell Size Endothelium, Corneal Humans Neural Networks, Computer Microscopy Image Interpretation, Computer-Assisted Databases, Factual Endothelial Cells Reproducibility of Results Predictive Value of Tests
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Phenotypic Clustering of Left Ventricular Diastolic Function Parameters: Patterns and Prognostic Relevance.

JACC. Cardiovascular imaging Apr 18, 2018
OBJECTIVES: This study sought to explore the natural clustering of echocardiographic variables used for assessing left ventricular (LV) diastolic dysfunction (DD) in order to isolate high-risk phenotypic patterns and assess their prognostic significa...
Diastole Echocardiography, Doppler, Color Echocardiography, Doppler, Pulsed Heart Ventricles Progression-Free Survival Ventricular Dysfunction, Left Image Interpretation, Computer-Assisted Pattern Recognition, Automated Aged Aged, 80 and over Male Ventricular Function, Left Middle Aged Risk Assessment Disease Progression Cluster Analysis Predictive Value of Tests Cause of Death Phenotype Retrospective Studies Female Risk Factors Hospitalization Humans Machine Learning
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Computer-aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI.

Journal of magnetic resonance imaging : JMRI Apr 16, 2018
BACKGROUND: Deep learning is the most promising methodology for automatic computer-aided diagnosis of prostate cancer (PCa) with multiparametric MRI (mp-MRI).
Humans Neural Networks, Computer Male Diagnosis, Computer-Assisted Deep Learning ROC Curve Predictive Value of Tests Software Databases, Factual Retrospective Studies Reproducibility of Results Sensitivity and Specificity Area Under Curve Prostatic Neoplasms Pattern Recognition, Automated Diffusion Magnetic Resonance Imaging
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Coronary CT Angiography-derived Fractional Flow Reserve: Machine Learning Algorithm versus Computational Fluid Dynamics Modeling.

Radiology Apr 10, 2018
Purpose To compare two technical approaches for determination of coronary computed tomography (CT) angiography-derived fractional flow reserve (FFR)-FFR derived from coronary CT angiography based on computational fluid dynamics (hereafter, FFR) and F...
Sensitivity and Specificity Male Middle Aged Coronary Angiography Hemodynamics Hydrodynamics Machine Learning Predictive Value of Tests Computed Tomography Angiography Algorithms Coronary Stenosis Retrospective Studies Fractional Flow Reserve, Myocardial Humans Female Reproducibility of Results
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Transcriptomics and machine learning predict diagnosis and severity of growth hormone deficiency.

JCI insight Apr 5, 2018
BACKGROUND: The effect of gene expression data on diagnosis remains limited. Here, we show how diagnosis and classification of growth hormone deficiency (GHD) can be achieved from a single blood sample using a combination of transcriptomics and rando...
Severity of Illness Index Gene Expression Profiling Transcriptome Case-Control Studies Adolescent Humans Machine Learning Biomarkers Female Male Human Growth Hormone Growth Disorders Child, Preschool Child ROC Curve Principal Component Analysis Healthy Volunteers Datasets as Topic Gene Regulatory Networks Polymorphism, Single Nucleotide Predictive Value of Tests
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Back to the future - The integration of big data with machine learning is re-establishing the importance of predictive correlations in ovarian cancer diagnostics and therapeutics.

Gynecologic oncology Mar 21, 2018
Predictive Value of Tests Humans Datasets as Topic Machine Learning Genetic Therapy Female Databases, Genetic Ovarian Neoplasms
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Detection of Pathological Voice Using Cepstrum Vectors: A Deep Learning Approach.

Journal of voice : official journal of the Voice Foundation Mar 19, 2018
OBJECTIVES: Computerized detection of voice disorders has attracted considerable academic and clinical interest in the hope of providing an effective screening method for voice diseases before endoscopic confirmation. This study proposes a deep-learn...
Sound Spectrography Female Adult Humans Speech Acoustics Male Reproducibility of Results Vocal Cords Middle Aged Retrospective Studies Aged Speech Production Measurement Diagnosis, Computer-Assisted Aged, 80 and over Voice Quality Deep Learning Young Adult Pilot Projects Dysphonia Support Vector Machine Predictive Value of Tests Signal Processing, Computer-Assisted Acoustics
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