AIMC Topic: Retrospective Studies

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Deep Learning Method for Automated Classification of Anteroposterior and Posteroanterior Chest Radiographs.

Journal of digital imaging Dec 1, 2019
Ensuring correct radiograph view labeling is important for machine learning algorithm development and quality control of studies obtained from multiple facilities. The purpose of this study was to develop and test the performance of a deep convolutio...
Reproducibility of Results Adult Sensitivity and Specificity Deep Learning Humans Databases, Factual Retrospective Studies Child Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic
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Deep Learning for Detection of Complete Anterior Cruciate Ligament Tear.

Journal of digital imaging Dec 1, 2019
Deep learning for MRI detection of sports injuries poses unique challenges. To address these difficulties, this study examines the feasibility and incremental benefit of several customized network architectures in evaluation of complete anterior cruc...
Retrospective Studies Female Reproducibility of Results Young Adult Humans Image Interpretation, Computer-Assisted Deep Learning Anterior Cruciate Ligament Injuries Adult Adolescent Anterior Cruciate Ligament Sensitivity and Specificity Athletic Injuries Magnetic Resonance Imaging Male Knee Joint
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OPTICAL COHERENCE TOMOGRAPHY BIOMARKERS TO DISTINGUISH DIABETIC MACULAR EDEMA FROM PSEUDOPHAKIC CYSTOID MACULAR EDEMA USING MACHINE LEARNING ALGORITHMS.

Retina (Philadelphia, Pa.) Dec 1, 2019
PURPOSE: In diabetic patients presenting with macular edema (ME) shortly after cataract surgery, identifying the underlying pathology can be challenging and influence management. Our aim was to develop a simple clinical classifier able to confirm a d...
Sensitivity and Specificity Male Middle Aged Diagnosis, Computer-Assisted Retrospective Studies Female Reproducibility of Results Humans Macular Edema Aged Diabetic Retinopathy Fluorescein Angiography Machine Learning Visual Acuity Subretinal Fluid Biomarkers Predictive Value of Tests Pseudophakia Area Under Curve Tomography, Optical Coherence
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Predicting Nondiagnostic Home Sleep Apnea Tests Using Machine Learning.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine Nov 15, 2019
STUDY OBJECTIVES: Home sleep apnea testing (HSAT) is an efficient and cost-effective method of diagnosing obstructive sleep apnea (OSA). However, nondiagnostic HSAT necessitates additional tests that erode these benefits, delaying diagnoses and incre...
Self Care Retrospective Studies Surveys and Questionnaires Humans Female Sensitivity and Specificity Sleep Apnea, Obstructive Aged Machine Learning Male Calibration Adult Decision Support Techniques Middle Aged Polysomnography
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Deep learning and medical diagnosis - Authors' reply.

Lancet (London, England) Nov 9, 2019
Deep Learning Medical Writing Algorithms Retrospective Studies Tomography, X-Ray Computed
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Deep learning and medical diagnosis.

Lancet (London, England) Nov 9, 2019
Machine Learning Algorithms Retrospective Studies Tomography, X-Ray Computed Deep Learning
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Deep learning and medical diagnosis.

Lancet (London, England) Nov 9, 2019
Algorithms Retrospective Studies Tomography, X-Ray Computed Deep Learning Machine Learning
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Relevant Features in Nonalcoholic Steatohepatitis Determined Using Machine Learning for Feature Selection.

Metabolic syndrome and related disorders Nov 1, 2019
We investigated the prevalence and the most relevant features of nonalcoholic steatohepatitis (NASH), a stage of nonalcoholic fatty liver disease, (NAFLD) in which the inflammation of hepatocytes can lead to increased cardiovascular risk, liver fibr...
Adult Sensitivity and Specificity Cross-Sectional Studies Male Middle Aged Disease Progression Prevalence Severity of Illness Index Prognosis Retrospective Studies Female Aged Humans Decision Making Machine Learning Diabetes Mellitus, Type 2 Algorithms Liver Cirrhosis Non-alcoholic Fatty Liver Disease Hypertension Metabolic Syndrome
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Real world evidence in cardiovascular medicine: ensuring data validity in electronic health record-based studies.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: With growing availability of digital health data and technology, health-related studies are increasingly augmented or implemented using real world data (RWD). Recent federal initiatives promote the use of RWD to make clinical assertions th...
Cardiology Machine Learning Humans Retrospective Studies Natural Language Processing Artificial Intelligence Electronic Health Records Data Mining Cardiovascular Diseases Datasets as Topic Information Storage and Retrieval
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Novel Machine Learning Approach to Identify Preoperative Risk Factors Associated With Super-Utilization of Medicare Expenditure Following Surgery.

JAMA surgery Nov 1, 2019
IMPORTANCE: Typically defined as the top 5% of health care users, super-utilizers are responsible for an estimated 40% to 55% of all health care costs. Little is known about which factors may be associated with increased risk of long-term postoperati...
Patient Acceptance of Health Care Male Risk Assessment United States Postoperative Care Elective Surgical Procedures Medicare Health Expenditures Preoperative Care Retrospective Studies Female Risk Factors Aged Humans Machine Learning
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