AIMC Topic: Severity of Illness Index

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Machine learning-based approach for disease severity classification of carpal tunnel syndrome.

Scientific reports Aug 31, 2021
Identifying the severity of carpal tunnel syndrome (CTS) is essential to providing appropriate therapeutic interventions. We developed and validated machine-learning (ML) models for classifying CTS severity. Here, 1037 CTS hands with 11 variables eac...
Humans Machine Learning Retrospective Studies Female Male Middle Aged Severity of Illness Index Body Mass Index Pain Measurement Neural Conduction Electrodiagnosis Carpal Tunnel Syndrome
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Artificial Intelligence Predicts Severity of COVID-19 Based on Correlation of Exaggerated Monocyte Activation, Excessive Organ Damage and Hyperinflammatory Syndrome: A Prospective Clinical Study.

Frontiers in immunology Aug 27, 2021
BACKGROUND: Prediction of the severity of COVID-19 at its onset is important for providing adequate and timely management to reduce mortality.
Middle Aged HMGB1 Protein Biomarkers Humans Severity of Illness Index Prognosis L-Lactate Dehydrogenase COVID-19 Diagnosis, Computer-Assisted Female Alanine Transaminase Macrophages Monocytes SARS-CoV-2 Aspartate Aminotransferases Support Vector Machine Cytokines Male Prospective Studies
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Deep Learning Algorithm Predicts Angiographic Coronary Artery Disease in Stable Patients Using Only a Standard 12-Lead Electrocardiogram.

The Canadian journal of cardiology Aug 20, 2021
BACKGROUND: Current electrocardiogram analysis algorithms cannot predict the presence of coronary artery disease (CAD), especially in stable patients. This study assessed the ability of an artificial intelligence algorithm (ECGio; HEARTio Inc, Pittsb...
Middle Aged Severity of Illness Index Deep Learning Electrocardiography Follow-Up Studies Coronary Vessels Fractional Flow Reserve, Myocardial Predictive Value of Tests Algorithms Coronary Angiography Retrospective Studies Humans Coronary Artery Disease Female Artificial Intelligence Aged Male
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Artificial intelligence to improve efficiency of administration of gross motor function assessment in children with cerebral palsy.

Developmental medicine and child neurology Aug 13, 2021
AIM: To create a reduced version of the 66-item Gross Motor Function Measure (rGMFM-66) using innovative artificial intelligence methods to improve efficiency of administration of the GMFM-66.
Child Support Vector Machine Cerebral Palsy Motor Skills Female Male Severity of Illness Index Adolescent Child, Preschool Neural Networks, Computer Artificial Intelligence Machine Learning Prospective Studies Retrospective Studies Humans
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Vesseg: An Open-Source Tool for Deep Learning-Based Atherosclerotic Plaque Quantification in Histopathology Images-Brief Report.

Arteriosclerosis, thrombosis, and vascular biology Aug 12, 2021
Objective: Manual plaque segmentation in microscopy images is a time-consuming process in atherosclerosis research and potentially subject to unacceptable user-to-user variability and observer bias. We address this by releasing Vesseg a tool that inc...
Mice, Inbred C57BL Predictive Value of Tests Atherosclerosis Microscopy Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Deep Learning Mice Staining and Labeling Disease Models, Animal Vascular Remodeling Mice, Knockout, ApoE Plaque, Atherosclerotic Arteries Software Female Reproducibility of Results Animals Male Severity of Illness Index
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Machine learning model for early prediction of acute kidney injury (AKI) in pediatric critical care.

Critical care (London, England) Aug 10, 2021
BACKGROUND: Acute kidney injury (AKI) in pediatric critical care patients is diagnosed using elevated serum creatinine, which occurs only after kidney impairment. There are no treatments other than supportive care for AKI once it has developed, so it...
Machine Learning Computer Simulation Acute Kidney Injury Female Infant, Newborn Young Adult Humans Critical Care Pediatrics Child, Preschool Child Intensive Care Units, Pediatric ROC Curve Area Under Curve Male Infant Severity of Illness Index Adolescent Cohort Studies
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Chronic kidney disease diagnosis using decision tree algorithms.

BMC nephrology Aug 9, 2021
BACKGROUND: Chronic Kidney Disease (CKD), i.e., gradual decrease in the renal function spanning over a duration of several months to years without any major symptoms, is a life-threatening disease. It progresses in six stages according to the severit...
Patient Acuity Early Diagnosis Medical Records Severity of Illness Index Humans Renal Insufficiency, Chronic Machine Learning Glomerular Filtration Rate Algorithms Kidney Function Tests Male Decision Trees Middle Aged Prognosis Disease Progression Female Reproducibility of Results
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Editorial: The National COVID Cohort Collaborative Consortium Combines Population Data with Machine Learning to Evaluate and Predict Risk Factors for the Severity of COVID-19.

Medical science monitor : international medical journal of experimental and clinical research Aug 2, 2021
Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19) commonly presents with pneumonia. However, COVID-19 is now recognized to involve multiple organ systems with varying severity ...
Humans Machine Learning Male Middle Aged Severity of Illness Index Diagnosis, Computer-Assisted Models, Statistical Population Health COVID-19 Female SARS-CoV-2 Risk Factors Adult
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Machine learning for detection of stenoses and aneurysms: application in a physiologically realistic virtual patient database.

Biomechanics and modeling in mechanobiology Jul 31, 2021
This study presents an application of machine learning (ML) methods for detecting the presence of stenoses and aneurysms in the human arterial system. Four major forms of arterial disease-carotid artery stenosis (CAS), subclavian artery stenosis (SAS...
Severity of Illness Index User-Computer Interface Peripheral Arterial Disease Aortic Aneurysm, Abdominal Regional Blood Flow Models, Biological Humans Neural Networks, Computer Carotid Stenosis Machine Learning Subclavian Artery Algorithms Databases, Factual Sensitivity and Specificity
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Automated machine learning optimizes and accelerates predictive modeling from COVID-19 high throughput datasets.

Scientific reports Jul 23, 2021
COVID-19 outbreak brings intense pressure on healthcare systems, with an urgent demand for effective diagnostic, prognostic and therapeutic procedures. Here, we employed Automated Machine Learning (AutoML) to analyze three publicly available high thr...
Interferon-gamma Signal Transduction Databases, Genetic Metabolomics Immunity, Innate Databases, Protein SARS-CoV-2 Software Severity of Illness Index COVID-19 Gene Expression Profiling Databases, Factual ROC Curve Humans Proteomics Machine Learning Biomarkers Computer Simulation Prognosis
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