AIMC Topic: Machine Learning

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Gut Microbiota in T1DM-Onset Pediatric Patients: Machine-Learning Algorithms to Classify Microorganisms as Disease Linked.

The Journal of clinical endocrinology and metabolism Sep 1, 2020
AIMS: The purpose of this work is to find the gut microbial fingerprinting of pediatric patients with type 1 diabetes.
Metagenome Cohort Studies Female Child, Preschool Risk Factors Child Male Feces Adolescent Humans Diabetes Mellitus, Type 1 Machine Learning Gastrointestinal Microbiome Algorithms Age of Onset
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Can Machine-learning Algorithms Predict Early Revision TKA in the Danish Knee Arthroplasty Registry?

Clinical orthopaedics and related research Sep 1, 2020
BACKGROUND: Revision TKA is a serious adverse event with substantial consequences for the patient. As the demand for TKA rises, reducing the risk of revision TKA is becoming increasingly important. Predictive tools based on machine-learning algorithm...
Knee Injuries Arthroplasty, Replacement, Knee Reoperation Preoperative Period Osteoarthritis, Knee Predictive Value of Tests Registries Body Weight Risk Assessment Adult Postoperative Complications Humans Algorithms Male Age Factors Machine Learning Female Denmark Middle Aged Risk Factors Aged
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Machine Learning for Work Disability Prevention: Introduction to the Special Series.

Journal of occupational rehabilitation Sep 1, 2020
Rapid development in computer technology has led to sophisticated methods of analyzing large datasets with the aim of improving human decision making. Artificial Intelligence and Machine Learning (ML) approaches hold tremendous potential for solving ...
Humans Artificial Intelligence Machine Learning Persons with Disabilities Workers' Compensation
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Machine Learning Within Studies of Early-Life Environmental Exposures and Child Health: Review of the Current Literature and Discussion of Next Steps.

Current environmental health reports Sep 1, 2020
PURPOSE OF REVIEW: The goal of this article is to review the use of machine learning (ML) within studies of environmental exposures and children's health, identify common themes across studies, and provide recommendations to advance their use in rese...
Humans Machine Learning Environmental Exposure Child Child Health Data Interpretation, Statistical Environmental Health
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Dynamic impact of transfusion ratios on outcomes in severely injured patients: Targeted machine learning analysis of the Pragmatic, Randomized Optimal Platelet and Plasma Ratios randomized clinical trial.

The journal of trauma and acute care surgery Sep 1, 2020
BACKGROUND: Massive transfusion protocols to treat postinjury hemorrhage are based on predefined blood product transfusion ratios followed by goal-directed transfusion based on patient's clinical evolution. However, it remains unclear how these trans...
Trauma Centers Intention to Treat Analysis Wounds and Injuries Hemostasis North America Machine Learning Female Male Hemorrhage Erythrocytes Humans Blood Platelets Plasma Blood Component Transfusion
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Leveraging Machine Learning to Identify Predictors of Receiving Psychosocial Treatment for Attention Deficit/Hyperactivity Disorder.

Administration and policy in mental health Sep 1, 2020
This study aimed to identify factors associated with receiving psychosocial treatment for ADHD in a nationally representative sample. Participants were 6630 youth with a parent-reported diagnosis of ADHD from the 2016-2017 National Survey of Children...
Attention Deficit Disorder with Hyperactivity Patient Acceptance of Health Care Child ROC Curve Socioeconomic Factors Female Risk Factors Male Comorbidity Severity of Illness Index Adolescent Child, Preschool Humans Machine Learning
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The Impact of Undersampling on the Predictive Performance of Logistic Regression and Machine Learning Algorithms: A Simulation Study.

Epidemiology (Cambridge, Mass.) Sep 1, 2020
Humans Machine Learning Selection Bias Algorithms Computer Simulation Logistic Models
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Intelligent Robotics Incorporating Machine Learning Algorithms for Improving Functional Capacity Evaluation and Occupational Rehabilitation.

Journal of occupational rehabilitation Sep 1, 2020
Introduction Occupational rehabilitation often involves functional capacity evaluations (FCE) that use simulated work tasks to assess work ability. Currently, there exists no single, streamlined solution to simulate all or a large number of standard ...
Humans Machine Learning Algorithms Robotics Occupational Health Rehabilitation
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Predicting Long-Term Outcomes After Poor-Grade Aneurysmal Subarachnoid Hemorrhage Using Decision Tree Modeling.

Neurosurgery Sep 1, 2020
BACKGROUND: Despite advances in the treatment of poor-grade aneurysmal subarachnoid hemorrhage (aSAH), predicting the long-term outcome of aSAH remains challenging, although essential.
Female Treatment Outcome Decision Trees Aged Humans Subarachnoid Hemorrhage Male Adult Machine Learning Middle Aged Prognosis ROC Curve Clinical Decision-Making Logistic Models
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Predicting Individual Remission After Electroconvulsive Therapy Based on Structural Magnetic Resonance Imaging: A Machine Learning Approach.

The journal of ECT Sep 1, 2020
OBJECTIVE: To identify important clinical or imaging features predictive of an individual's response to electroconvulsive therapy (ECT) by utilizing a machine learning approach.
Humans Machine Learning Brain Female Magnetic Resonance Imaging Predictive Value of Tests Remission Induction Electroconvulsive Therapy Aged Male Middle Aged Depressive Disorder, Major
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