AIMC Topic: Risk Assessment
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Spatiotemporal evolution and risk thresholds of PM components in China from the human health perspective.
Environmental pollution (Barking, Essex : 1987)
Apr 2, 2025
PM is a significant global public health hazard, with its components closely linked to various fatal diseases, thereby significantly increasing mortality rates. This study analysed the spatiotemporal evolution of PM-related mortality and death rates ...
Improved prediction and risk stratification of major adverse cardiovascular events using an explainable machine learning approach combining plasma biomarkers and traditional risk factors.
Cardiovascular diabetology
Apr 2, 2025
BACKGROUND: Cardiovascular diseases (CVD) remain the leading cause of morbidity and mortality globally. Traditional risk models, primarily based on established risk factors, often lack the precision needed to accurately predict new-onset major advers...
90-day mortality prediction in elective visceral surgery using machine learning: a retrospective multicenter development, validation, and comparison study.
International journal of surgery (London, England)
Apr 1, 2025
BACKGROUND: Machine Learning (ML) is increasingly being adopted in biomedical research, however, its potential for outcome prediction in visceral surgery remains uncertain. This study compares the potential of ML methods for preoperative 90-day morta...
Individualized dynamic risk assessment and treatment selection for multiple myeloma.
British journal of cancer
Apr 1, 2025
BACKGROUND: Individualized treatment decisions for multiple myeloma (MM) patients require accurate risk stratification that accounts for patient-specific consequences of cytogenetic abnormalities on disease progression.
Application of type-2 heptagonal fuzzy sets with multiple operators in multi-criteria decision-making for identifying risk factors of Zika virus.
BMC infectious diseases
Apr 1, 2025
PURPOSE: This study aims to identify and rank the key risk factors associated with the Zika virus by leveraging a novel multi-criteria decision-making (MCDM) framework based on type-2 heptagonal fuzzy sets. By integrating advanced aggregation operato...
Cardiometabolic index predicts cardiovascular events in aging population: a machine learning-based risk prediction framework from a large-scale longitudinal study.
Frontiers in endocrinology
Apr 1, 2025
BACKGROUND: While the Cardiometabolic Index (CMI) serves as a novel marker for assessing adipose tissue distribution and metabolic function, its prognostic utility for cardiovascular disease (CVD) events remains incompletely understood. This investig...
AI-Quantitative CT Coronary Plaque Features Associate With a Higher Relative Risk in Women: CONFIRM2 Registry.
Circulation. Cardiovascular imaging
Mar 31, 2025
BACKGROUND: Coronary plaque features are imaging biomarkers of cardiovascular risk, but less is known about sex-specific patterns in their prognostic value. This study aimed to define sex differences in the coronary atherosclerotic phenotypes assesse...
Natural language processing for identifying major bleeding risk in hospitalised medical patients.
Computers in biology and medicine
Mar 30, 2025
BACKGROUND: Major bleeding is a severe complication in critically ill medical patients, resulting in significant morbidity, mortality, and healthcare costs. This study aims to assess the incidence and risk factors for major bleeding in hospitalised m...
The environmental risk of heterogeneous oxidation is unneglectable: Time-resolved assessments beyond typical intermediate investigation.
Water research
Mar 29, 2025
The safety of advanced oxidation processes is paramount, surpassing treatment efficiency concerns. However, current research is limited to the qualitative toxicity investigations of targeted contaminants by-products, while the detoxification effects ...
Accurate prediction of mediolateral episiotomy risk during labor: development and verification of an artificial intelligence model.
BMC pregnancy and childbirth
Mar 29, 2025
OBJECTIVE: The study developed an intelligent online evaluation system for mediolateral episiotomy, which incorporated machine learning algorithms and integrated maternal physiological data collected during delivery.
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