AIMC Topic: Risk Assessment

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Incorporation of Metabolic Dysfunction-Associated Steatotic Liver Disease in the Health Stage of Cardiovascular-Kidney-Metabolic Syndrome Improves Predictive Ability for Coronary Artery Disease in a Japanese General Population.

Journal of the American Heart Association
BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome is a recently proposed condition encompassing metabolic dysfunction, chronic kidney disease, and cardiovascular diseases including coronary artery disease (CAD). Although concomitant metaboli...

Machine learningdriven framework for realtime air quality assessment and predictive environmental health risk mapping.

Scientific reports
This research introduces a practical and innovative approach for real-time air quality assessment and health risk prediction, focusing on urban, industrial, suburban, rural, and traffic-heavy environments. The framework integrates data from multiple ...

Probability-Based Early Warning for Seasonal Influenza in China: Model Development Study.

JMIR medical informatics
BACKGROUND: Seasonal influenza is a major global public health concern, leading to escalated morbidity and mortality rates. Traditional early warning models rely on binary (0/1) classification methods, which issue alerts only when predefined threshol...

Development and validation of a novel public prediction platform for deciduous caries in preschool children: an observational study from Northwest China.

BMC pediatrics
BACKGROUND: Early childhood caries (ECC) is a major global public health concern, necessitating its early screening. This study aimed to establish a caries risk assessment (CRA) platform for managing caries in community preschool children in underdev...

Development and interpretation of a machine learning risk prediction model for post-stroke depression in a Chinese population.

Scientific reports
Current evidence for predictive models of post-stroke depression (PSD) risk based on machine learning (ML) remains limited. The aim of this study is to develop a superior predictive model based on ML algorithms for PSD in the Chinese population. We r...

Machine learning algorithms to predict the risk of admission to intensive care units in HIV-infected individuals: a single-centre study.

Virology journal
Antiretroviral therapy (ART) has transformed HIV from a rapidly progressive and fatal disease to a chronic disease with limited impact on life expectancy. However, people living with HIV(PLWHs) faced high critical illness risk due to the increased pr...

Machine learning enables legal risk assessment in internet healthcare using HIPAA data.

Scientific reports
This study explores how artificial intelligence technologies can enhance the regulatory capacity for legal risks in internet healthcare based on a machine learning (ML) analytical framework and utilizes data from the health insurance portability and ...

Personalized colorectal cancer risk assessment through explainable AI and Gut microbiome profiling.

Gut microbes
The clinical adenoma - carcinoma progression represents a well-established framework for understanding colorectal cancer (CRC) development, although the molecular mechanisms underlying this transition remain only partially understood. Increasing evid...

Machine learning algorithms for risk factor selection with application to 60-day sepsis morbidity risk for a geriatric hip fracture cohort.

BMC geriatrics
BACKGROUND: Sepsis after hip fracture in elderly people is a risk factor for mortality. The purpose of this study was to screen for risk factors for 60-day sepsis morbidity after hip fracture and to establish a predictive model using various machine ...

Novel risk factors and personalized risk calculator for predicting proximal junctional kyphosis after adult spinal deformity surgery.

The bone & joint journal
AIMS: Proximal junctional kyphosis (PJK) is a prevalent and detrimental complication associated with corrective surgery for adult spinal deformity (ASD). While existing predictive models have been able to predict PJK, they have lacked individualized ...