AIMC Topic: Risk Assessment

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Urban-rural disparities in fall risk among older Chinese adults: insights from machine learning-based predictive models.

Frontiers in public health
BACKGROUND: Falls among older adults are a significant challenge to global healthy aging. Identifying key factors and differences in fall risks, along with developing predictive models, is essential for differentiated and precise interventions in Chi...

Transfer learning for mortality risk: A case study on the United Kingdom.

PloS one
This study introduces a transfer learning framework to address data scarcity in mortality risk prediction for the UK, where local mortality data is unavailable. By leveraging a pretrained model built from data across eight countries (excluding the UK...

Comprehensive Machine Learning-Based Prediction Model for Delirium Risk in Older Patients with Dementia: Risk Factors Identification.

Clinical interventions in aging
BACKGROUND: Delirium superimposed on dementia (DSD) is a severe complication in older adults with dementia, marked by fluctuating cognition, inattention, and altered consciousness. Detection is challenging due to symptom overlap, yet it contributes t...

Cytopathological quantification of NORs using artificial intelligence to oral cancer screening.

Brazilian oral research
Oral squamous cell carcinoma (OSCC) remains the most prevalent neoplasm of the head and neck. In recent decades, the incidence and prevalence of OSCC have not significantly changed, highlighting the critical need to develop and implement new risk ass...

All-Cause Mortality Risk in Elderly Patients with Femoral Neck and Intertrochanteric Fractures: A Predictive Model Based on Machine Learning.

Clinical interventions in aging
INTRODUCTION: The aim of this study was to identify the influencing factors for all-cause mortality in elderly patients with intertrochanteric and femoral neck fractures and to construct predictive models.

[Artificial intelligence in assessment of individual risks of age-related macular degeneration progression].

Vestnik oftalmologii
Age-related macular degeneration (AMD) is a progressive degenerative retinal disease and a leading cause of blindness in older adults worldwide. According to numerous studies, the number of affected individuals reached 196 million in 2020, with proje...

Identifying high-dose opioid prescription risks using machine learning: A focus on sociodemographic characteristics.

Journal of opioid management
OBJECTIVE: The objective of this study was to leverage machine learning techniques to analyze administrative claims and socioeconomic data, with the aim of identifying and interpreting the risk factors associated with high-dose opioid prescribing.

Clinical Application of a Big Data Machine Learning Analysis Model for Osteoporotic Fracture Risk Assessment Built on Multicenter Clinical Data in Qingdao City.

Discovery medicine
BACKGROUND: Osteoporotic fractures (OPF) pose a public health issue, imposing significant burdens on families and societies worldwide. Currently, there is a lack of comprehensive and validated risk assessment models for OPF. This study aims to develo...

Machine Learning Approaches for Neuroblastoma Risk Prediction and Stratification.

Critical reviews in oncogenesis
Machine learning (ML) holds great promise in advancing risk prediction and stratification for neuroblastoma, a highly heterogeneous pediatric cancer. By utilizing large-scale biological and clinical data, ML models can detect complex patterns that tr...

Machine learning-enabled risk prediction of self-neglect among community-dwelling older adults in China.

Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
BACKGROUND: Elder self-neglect (ESN) is usually ignored as a private problem and impairs the health outcomes of older adults. It is essential to construct a robust and efficient tool for risk prediction which can better detect and prevent self-neglec...