AIMC Topic: Risk

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A deep learning approach for lower back-pain risk prediction during manual lifting.

PloS one Feb 19, 2021
Occupationally-induced back pain is a leading cause of reduced productivity in industry. Detecting when a worker is lifting incorrectly and at increased risk of back injury presents significant possible benefits. These include increased quality of li...
Male Deep Learning Low Back Pain Risk Lifting Humans Female Adult
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DeepCompete : A deep learning approach to competing risks in continuous time domain.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 25, 2021
An increasing number of people survive longer ages leading to a growing population of people 65 years of age or older. A large percentage of this population is afflicted with multiple acute diseases (multi-morbidity). Clinicians need new tools to qua...
Survival Analysis Humans Risk Aged Deep Learning Models, Statistical
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Machine Learning Algorithms Predict Clinically Significant Improvements in Satisfaction After Hip Arthroscopy.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association Dec 24, 2020
PURPOSE: To develop machine learning algorithms to predict failure to achieve clinically significant satisfaction after hip arthroscopy.
Hip Calibration Humans Arthroscopy Neural Networks, Computer Postoperative Period Case-Control Studies Risk Machine Learning ROC Curve Young Adult Treatment Outcome Algorithms Adult Patient Satisfaction Male Female
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Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging, and Test Data: Diagnostic Model Development.

Journal of medical Internet research Dec 16, 2020
BACKGROUND: Assigning meaningful probabilities of SARS-CoV-2 infection risk presents a diagnostic challenge across the continuum of care.
COVID-19 Testing Probability California Risk Cough Female Bayes Theorem Aged Benchmarking Aged, 80 and over Fever Male Symptom Assessment Middle Aged Prevalence Humans Comorbidity Machine Learning Decision Support Systems, Clinical COVID-19
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Artificial Intelligence in Coronary Computed Tomography Angiography: From Anatomy to Prognosis.

BioMed research international Dec 16, 2020
Cardiac computed tomography angiography (CCTA) is widely used as a diagnostic tool for evaluation of coronary artery disease (CAD). Despite the excellent capability to rule-out CAD, CCTA may overestimate the degree of stenosis; furthermore, CCTA anal...
Plaque, Atherosclerotic Computed Tomography Angiography Machine Learning Coronary Stenosis Humans Middle Aged Fractional Flow Reserve, Myocardial Algorithms Artificial Intelligence Diagnosis, Computer-Assisted Calcium Phenotype Image Processing, Computer-Assisted Coronary Vessels Prognosis Coronary Artery Disease Myocardial Ischemia Risk
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Potential predictors of type-2 diabetes risk: machine learning, synthetic data and wearable health devices.

BMC bioinformatics Dec 14, 2020
BACKGROUND: The aim of a recent research project was the investigation of the mechanisms involved in the onset of type 2 diabetes in the absence of familiarity. This has led to the development of a computational model that recapitulates the aetiology...
Risk Wearable Electronic Devices User-Computer Interface Diabetes Mellitus, Type 2 Models, Theoretical Humans Machine Learning Female Aged Adult Male Middle Aged
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Machine learning to reveal hidden risk combinations for the trajectory of posttraumatic stress disorder symptoms.

Scientific reports Dec 10, 2020
The nature of the recovery process of posttraumatic stress disorder (PTSD) symptoms is multifactorial. The Massive Parallel Limitless-Arity Multiple-testing Procedure (MP-LAMP), which was developed to detect significant combinational risk factors com...
Humans Machine Learning Female Middle Aged Severity of Illness Index Stress Disorders, Post-Traumatic Unemployment Risk Factors Aged Adult Male Emergency Shelter Predictive Value of Tests Walking Rest Risk
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Using the National Trauma Data Bank (NTDB) and machine learning to predict trauma patient mortality at admission.

PloS one Nov 17, 2020
A 400-estimator gradient boosting classifier was trained to predict survival probabilities of trauma patients. The National Trauma Data Bank (NTDB) provided 799233 complete patient records (778303 survivors and 20930 deaths) each containing 32 featur...
Risk Wounds and Injuries Glasgow Coma Scale Reproducibility of Results Probability Hospitalization Sex Factors ROC Curve Humans False Positive Reactions Heart Rate Injury Severity Score Machine Learning Algorithms Databases, Factual
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Prediction and prioritization of autism-associated long non-coding RNAs using gene expression and sequence features.

BMC bioinformatics Nov 7, 2020
BACKGROUND: Autism spectrum disorders (ASD) refer to a range of neurodevelopmental conditions, which are genetically complex and heterogeneous with most of the genetic risk factors also found in the unaffected general population. Although all the cur...
Risk Autism Spectrum Disorder Brain Transcriptome RNA, Long Noncoding Humans Machine Learning
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A Web Application for Adrenal Incidentaloma Identification, Tracking, and Management Using Machine Learning.

Applied clinical informatics Sep 16, 2020
BACKGROUND: Incidental radiographic findings, such as adrenal nodules, are commonly identified in imaging studies and documented in radiology reports. However, patients with such findings frequently do not receive appropriate follow-up, partially due...
Machine Learning Software Databases, Factual Natural Language Processing Radiography Internet Medical Informatics Risk Humans Incidental Findings Adrenal Gland Diseases
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