AI Medical Compendium Topic:
Risk Factors

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An analytical review on the use of artificial intelligence and machine learning in diagnosis, prediction, and risk factor analysis of multiple sclerosis.

Multiple sclerosis and related disorders
Medical research offers potential for disease prediction, like Multiple Sclerosis (MS). This neurological disorder damages nerve cell sheaths, with treatments focusing on symptom relief. Manual MS detection is time-consuming and error prone. Though M...

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods.

Scientific reports
By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with me...

[Relationship between certain uses of artificial intelligence and psychosocial risk factors in European work environments].

Archivos de prevencion de riesgos laborales
INTRODUCTION: To examine the relationship between the use of Artificial Intelligence (AI) to assess and monitor job performance and exposure to psychosocial risk factors, as well as associated adverse health effects in the European work environment.

Promoting safety of underground machinery operators through participatory ergonomics and fuzzy model analysis to foster sustainable mining practices.

Scientific reports
One of the most vital parameters to achieve sustainability in any field is encompassing the Occupational Health and Safety (OHS) of the workers. In mining industry where heavy earth moving machineries are largely employed, ergonomic hazards turn out ...

An assessment of the value of deep neural networks in genetic risk prediction for surgically relevant outcomes.

PloS one
INTRODUCTION: Postoperative complications affect up to 15% of surgical patients constituting a major part of the overall disease burden in a modern healthcare system. While several surgical risk calculators have been developed, none have so far been ...

Identifying high-risk Fontan phenotypes using K-means clustering of cardiac magnetic resonance-based dyssynchrony metrics.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Individuals with a Fontan circulation encompass a heterogeneous group with adverse outcomes linked to ventricular dilation, dysfunction, and dyssynchrony. The purpose of this study was to assess if unsupervised machine learning cluster an...

Semi-supervised Double Deep Learning Temporal Risk Prediction (SeDDLeR) with Electronic Health Records.

Journal of biomedical informatics
BACKGROUND: Risk prediction plays a crucial role in planning for prevention, monitoring, and treatment. Electronic Health Records (EHRs) offer an expansive repository of temporal medical data encompassing both risk factors and outcome indicators esse...

Regularized ensemble learning for prediction and risk factors assessment of students at risk in the post-COVID era.

Scientific reports
The COVID-19 pandemic has had a significant impact on students' academic performance. The effects of the pandemic have varied among students, but some general trends have emerged. One of the primary challenges for students during the pandemic has bee...

Predictors of left atrial appendage thrombus in atrial fibrillation patients undergoing cardioversion.

Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing
BACKGROUND: Atrial fibrillation and atrial flutter represent the most prevalent clinically significant cardiac arrhythmias. While the CHA2DS2-VASc score is commonly used to inform anticoagulation therapy decisions for patients with these conditions, ...