AIMC Topic: Risk Factors

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Factors Contributing to Fatalities in Helicopter Emergency Medical Service Accidents.

Aerospace medicine and human performance
INTRODUCTION: This study aimed to update and reinforce previous research on helicopter emergency medical service accidents in the United States. By investigating predictors of fatalities after helicopter emergency medical service crashes through the ...

Identifying Preliminary Risk Profiles for Dissociation in 16- to 25-Year-Olds Using Machine Learning.

Early intervention in psychiatry
INTRODUCTION: Dissociation is associated with clinical severity, increased risk of suicide and self-harm, and disproportionately affects adolescents and young adults. Whilst evidence indicates multiple factors contribute to dissociative experiences, ...

Constructing a Predictive Model for Psychological Distress of Young- and Middle-Aged Gynaecological Cancer Patients.

Journal of evaluation in clinical practice
BACKGROUND: Cancer patients experience substantial psychological distress which causes the reduction of the quality of life. However, the risk of psychological distress has not been well predicted especially in young- and middle-aged gynaecological c...

Application of artificial intelligence and machine learning for risk stratification acute kidney injury among hematopoietic stem cell transplantation patients: PCRRT ICONIC AI Initiative Group Meeting Proceedings.

Clinical nephrology
Acute kidney injury (AKI) is a frequent, severe complication of hematopoietic stem cell transplantation (HSCT) and is associated with an increased risk of morbidity and mortality. Recent advances in artificial intelligence (AI) and machine learning (...

Machine Learning Model Predictors of Intrapleural Tissue Plasminogen Activator and DNase Failure in Pleural Infection: A Multicenter Study.

Annals of the American Thoracic Society
Intrapleural enzyme therapy (IET) with tissue plasminogen activator (tPA) and DNase has been shown to reduce the need for surgical intervention for complicated parapneumonic effusion/empyema (CPPE/empyema). Failure of IET may lead to delayed care an...

Application of machine learning for detecting high fall risk in middle-aged workers using video-based analysis of the first 3 steps.

Journal of occupational health
OBJECTIVES: Falls are among the most prevalent workplace accidents, necessitating thorough screening for susceptibility to falls and customization of individualized fall prevention programs. The aim of this study was to develop and validate a high fa...

Artificial Intelligence in Predicting Ocular Hypertension After Descemet Membrane Endothelial Keratoplasty.

Investigative ophthalmology & visual science
PURPOSE: Descemet membrane endothelial keratoplasty (DMEK) has emerged as a novel approach in corneal transplantation over the past two decades. This study aims to identify predisposing risk factors for post-DMEK ocular hypertension (OHT) and develop...

Development and validation of an interpretable longitudinal preeclampsia risk prediction using machine learning.

PloS one
Preeclampsia is a pregnancy-specific disease characterized by new onset hypertension after 20 weeks of gestation that affects 2-8% of all pregnancies and contributes to up to 26% of maternal deaths. Despite extensive clinical research, current predic...

Machine learning-based coronary heart disease diagnosis model for type 2 diabetes patients.

Frontiers in endocrinology
BACKGROUND: To establish a classification model for assisting the diagnosis of type 2 diabetes mellitus (T2DM) complicated with coronary heart disease (CHD).