AIMC Topic: Risk Assessment

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Fibro predict a machine learning risk score for advanced liver fibrosis in the general population using Israeli electronic health records.

Scientific reports
Liver diseases, notably cirrhosis, pose a substantial global health challenge, resulting in millions of annual deaths. Existing diagnostic methods primarily target high-risk groups, leaving a significant portion of patients undiagnosed. This study ai...

A fuzzy based hybrid approach for risk assessment of anesthesiologists using OPA and EDAS methods.

Scientific reports
Anesthesiologists are exposed to numerous occupational hazards due to the demanding nature of their profession and the complex environment in which they operate. Classical risk assessment approaches often fall short in addressing the multidimensional...

Development of the Screen for Child Anxiety Related Emotional Disorders (SCARED) optimal short scale for Chinese children and adolescents: based on FasterRisk machine learning modeling.

BMC public health
BACKGROUND: Although the Screen for Child Anxiety Related Emotional Disorders (SCARED) is a widely used tool for assessing anxiety, its 41-item format makes it a time-intensive method for identifying children and adolescents at high risk of anxiety. ...

Predicting the risk of threatened abortion using machine learning methods: a comparative study.

BMC pregnancy and childbirth
BACKGROUND AND OBJECTIVE: Threatened abortion, a common pregnancy complication that often leading to abortion, is hard to predict due to its non-specific symptoms and difficulty in differentiating from other early pregnancy bleeding causes. Current d...

Integrating multiple feature assessment methods to identify key predictors of repeat suicide attempts in Taiwan.

BMC psychiatry
BACKGROUND: The high rate of repeat attempts among individuals who have previously attempted suicide presents a critical challenge in public health and suicide prevention. While early and targeted intervention is crucial for this high-risk group, eff...

Synthetic data generation method improves risk prediction model for early tumor recurrence after surgery in patients with pancreatic cancer.

Scientific reports
Pancreatic cancer is aggressive with high recurrence rates, necessitating accurate prediction models for effective treatment planning, particularly for neoadjuvant chemotherapy or upfront surgery. This study explores the use of variational autoencode...

Predicting survival factor following suicide attempt in Iran: an ensemble machine learning technique.

BMC psychiatry
BACKGROUND: Suicide represents a significant challenge to public health that calls for a suitable intervention from the healthcare sector. Despite the typically low suicide rate among most Muslim nations, research indicates that there is an increase ...

Fire risk to structures in California's Wildland-Urban Interface.

Nature communications
The destructive impacts of wildfires on people, property and the environment have dramatically increased, especially in the Wildland-Urban Interface (WUI) in California. In these areas structures are threatened by both approaching flames and lofted e...

A data-intensive framework for evaluating ecological and human health impacts of soil potentially toxic elements (PTEs) in the mining-endemic region of Singida, Tanzania.

Environmental geochemistry and health
Uncontrolled soil contamination by potentially toxic elements (PTEs) poses serious threats to environmental and public health in mining-intensive regions. Against this background, this study assessed the distribution, sources, ecological impact, and ...

A Machine Learning Algorithm With an Oversampling Technique in Limited Data Scenarios for the Prediction of Present and Future Restorative Treatment Need: Development and Validation Study.

JMIR medical informatics
BACKGROUND: Untreated dental caries is the most common health condition worldwide. Therefore, new strategies need to be developed to reduce the manifestations of dental caries.