AIMC Topic: Sensitivity and Specificity

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Empirical assessment of bias in machine learning diagnostic test accuracy studies.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2020
OBJECTIVE: Machine learning (ML) diagnostic tools have significant potential to improve health care. However, methodological pitfalls may affect diagnostic test accuracy studies used to appraise such tools. We aimed to evaluate the prevalence and rep...
Biomedical Research Bias Systematic Reviews as Topic Publications Humans Diagnostic Techniques and Procedures Machine Learning Sensitivity and Specificity
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Deep learning to distinguish pancreatic cancer tissue from non-cancerous pancreatic tissue: a retrospective study with cross-racial external validation.

The Lancet. Digital health Jun 1, 2020
BACKGROUND: The diagnostic performance of CT for pancreatic cancer is interpreter-dependent, and approximately 40% of tumours smaller than 2 cm evade detection. Convolutional neural networks (CNNs) have shown promise in image analysis, but the networ...
Radiographic Image Enhancement Humans Deep Learning Aged Retrospective Studies Sensitivity and Specificity Pancreatic Neoplasms Tomography, X-Ray Computed Contrast Media Male Radiographic Image Interpretation, Computer-Assisted Female Middle Aged Taiwan Pancreas Reproducibility of Results Diagnosis, Differential Racial Groups
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Developing specific reporting guidelines for diagnostic accuracy studies assessing AI interventions: The STARD-AI Steering Group.

Nature medicine Jun 1, 2020
Guidelines as Topic Diagnostic Techniques and Procedures ROC Curve Predictive Value of Tests Area Under Curve Humans Research Report Artificial Intelligence Sensitivity and Specificity
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Thyroid Nodule Malignancy Risk Stratification Using a Convolutional Neural Network.

Ultrasound quarterly Jun 1, 2020
This study evaluates the performance of convolutional neural networks (CNNs) in risk stratifying the malignant potential of thyroid nodules alongside traditional methods such as American College of Radiology Thyroid Imaging Reporting and Data System ...
Image Interpretation, Computer-Assisted Biopsy, Fine-Needle Middle Aged Risk Assessment Thyroid Gland Thyroid Nodule Humans Neural Networks, Computer Retrospective Studies Female Sensitivity and Specificity Male
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Performance of deep neural network-based artificial intelligence method in diabetic retinopathy screening: a systematic review and meta-analysis of diagnostic test accuracy.

European journal of endocrinology Jun 1, 2020
OBJECTIVE: Automatic diabetic retinopathy screening system based on neural networks has been used to detect diabetic retinopathy (DR). However, there is no quantitative synthesis of performance of these methods. We aimed to estimate the sensitivity a...
Humans Diabetic Retinopathy Fundus Oculi Macular Edema Neural Networks, Computer Artificial Intelligence Sensitivity and Specificity Mass Screening
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Automated MRI-Based Deep Learning Model for Detection of Alzheimer's Disease Process.

International journal of neural systems Jun 1, 2020
In the context of neuro-pathological disorders, neuroimaging has been widely accepted as a clinical tool for diagnosing patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). The advanced deep learning method, a novel brain imagi...
Humans Female Models, Neurological Deep Learning Alzheimer Disease Cognitive Dysfunction Datasets as Topic Support Vector Machine Neuroimaging Aged Magnetic Resonance Imaging Aged, 80 and over Sensitivity and Specificity Male
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Automated Segmentation of Left Ventricular Myocardium on Cardiac Computed Tomography Using Deep Learning.

Korean journal of radiology Jun 1, 2020
OBJECTIVE: To evaluate the accuracy of a deep learning-based automated segmentation of the left ventricle (LV) myocardium using cardiac CT.
Middle Aged Deep Learning Coronary Artery Disease Humans Heart Ventricles Algorithms Automation Female Retrospective Studies Aged Tomography, X-Ray Computed Sensitivity and Specificity Male
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Incorporating natural language processing to improve classification of axial spondyloarthritis using electronic health records.

Rheumatology (Oxford, England) May 1, 2020
OBJECTIVES: To develop classification algorithms that accurately identify axial SpA (axSpA) patients in electronic health records, and compare the performance of algorithms incorporating free-text data against approaches using only International Clas...
Cohort Studies Natural Language Processing Area Under Curve Quality Improvement Aged International Classification of Diseases Sensitivity and Specificity Humans Spondylitis, Ankylosing Male Algorithms Spondylarthritis Middle Aged Electronic Health Records Female
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Diagnosing Glaucoma With Spectral-Domain Optical Coherence Tomography Using Deep Learning Classifier.

Journal of glaucoma Apr 1, 2020
UNLABELLED: PRéCIS:: A spectral-domain optical coherence tomography (SD-OCT) based deep learning system detected glaucomatous structural change with high sensitivity and specificity. It outperformed the clinical diagnostic parameters in discriminatin...
Adult Humans Visual Fields Sensitivity and Specificity Glaucoma Middle Aged Tomography, Optical Coherence Intraocular Pressure Female Deep Learning Nerve Fibers Male Aged ROC Curve Optic Disk Area Under Curve Retinal Ganglion Cells
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Depression screening using mobile phone usage metadata: a machine learning approach.

Journal of the American Medical Informatics Association : JAMIA Apr 1, 2020
OBJECTIVE: Depression is currently the second most significant contributor to non-fatal disease burdens globally. While it is treatable, depression remains undiagnosed in many cases. As mobile phones have now become an integral part of daily life, th...
Algorithms Area Under Curve Depression Humans Adult Telemedicine Surveys and Questionnaires Neural Networks, Computer Sensitivity and Specificity Depressive Disorder Mobile Applications Severity of Illness Index Machine Learning Cell Phone Use Logistic Models
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