AIMC Topic: Risk Factors

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Fuzzy and spatial analysis of cutaneous leishmaniasis in Pará State, Brazilian Amazon: an ecological and exploratory study.

Journal of infection in developing countries
INTRODUCTION: This study sought to analyze the relationships between cutaneous leishmaniasis and its epidemiological, environmental and socioeconomic conditions, in the 22 microregions of Pará state, Brazil, for the period from 2017 to 2022.

Predicting adverse birth outcome among childbearing women in Sub-Saharan Africa: employing innovative machine learning techniques.

BMC public health
BACKGROUND: Adverse birth outcomes, including preterm birth, low birth weight, and stillbirth, remain a major global health challenge, particularly in developing regions. Understanding the possible risk factors is crucial for designing effective inte...

Anticipating influential factors on suicide outcomes through machine learning techniques: Insights from a suicide registration program in western Iran.

Asian journal of psychiatry
Suicide is a global public health concern, with increasing rates observed in various regions, including Iran. This study focuses on the province of Hamadan, Iran, where suicide rates have been on the rise. The research aims to predict factors influen...

Evaluating GenAI systems to combat mental health issues in healthcare workers: An integrative literature review.

International journal of medical informatics
BACKGROUND: Mental health issues among healthcare workers remain a serious problem globally. Recent surveys continue to report high levels of depression, anxiety, burnout and other conditions amongst various occupational groups. Novel approaches are ...

Off-Label use of Woven EndoBridge device for intracranial brain aneurysm treatment: Modeling of occlusion outcome.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
INTRODUCTION: The Woven EndoBridge (WEB) device is emerging as a novel therapy for intracranial aneurysms, but its use for off-label indications requires further study. Using machine learning, we aimed to develop predictive models for complete occlus...

Reduced response to regadenoson with increased weight: An artificial intelligence-based quantitative myocardial perfusion study.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: There is conflicting evidence regarding the response to a fixed dose of regadenoson in patients with high body weight. The aim of this study was to evaluate the effectiveness of regadenoson in patients with varying body weights using nove...

Predicting Intimate Partner Violence Perpetration Among Young Adults Experiencing Homelessness in Seven U.S. Cities Using Interpretable Machine Learning.

Journal of interpersonal violence
Young adults experiencing homelessness (YAEH) are at higher risk for intimate partner violence (IPV) victimization than their housed peers. This is often due to their increased vulnerability to abuse and victimization before and during homelessness, ...

Machine learning computational model to predict lung cancer using electronic medical records.

Cancer epidemiology
BACKGROUND: Lung cancer (LC) screening using low-dose computed tomography (CT) is recommended according to standard risk criteria or personalized risk calculators. Machine learning (ML) models that can predict disease risk are an emerging method in m...