AIMC Topic: Risk Factors

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Semi-Supervised Fatty Liver Classification Using Attention-Based Graph Neural Network Models.

Journal of Korean medical science
BACKGROUND: Fatty liver disease is a common condition linked to metabolic syndrome, cardiovascular diseases, and liver cirrhosis, and timely, accurate diagnosis is crucial. In clinical studies, incorporating deep learning models often faces the chall...

Development of Venous Thromboembolism Risk Prediction Models Based on Whole Blood Gene Expression Profiling Using 20 Machine Learning Algorithms: Comprehensive Analysis Study.

JMIR medical informatics
BACKGROUND: There is a lack of venous thromboembolism (VTE) risk prediction models based on gene expression information. OBJECTIVE: This study aimed to construct a VTE prediction model based on whole blood gene expression profiling, by performing a c...

External validation of the IHXGboost-P model to predict incisional hernia after midline laparotomy.

Hernia : the journal of hernias and abdominal wall surgery
BACKGROUND: Incisional hernia (IH) is a significant complication that occurs after midline laparotomy and is associated with high morbidity and economic impacts. A fundamental goal of preventing IH is to determine which patients are considered low- o...

Development and external validation of an interpretable machine learning-based model for obesity risk prediction in 2-18-year-old children and adolescents in Beijing and Tangshan.

Journal of global health
BACKGROUND: The multifactorial mechanisms driving childhood obesity, a global public health challenge, are yet to be fully elucidated. We aimed to develop and externally validate three widely applied machine learning models alongside logistic regress...

Radiomics profiling combined with clinical risk factors for preoperative Lymphatic Metastasis prediction in Colorectal cancer: A multicenter study.

PloS one
PURPOSE: Accurate preoperative assessment of regional lymphatic metastases (LNM) is essential for effective surgical selection of patients with colorectal cancer (CRC). This study aimed to develop a machine learning (ML) model that integrates radiomi...

Environment and CVD: moving from Risk Prediction to Risk Management.

Current atherosclerosis reports
PURPOSE OF REVIEW: We attempt to provide a framework for cardiovascular risk assessment related to environmental pollutants to enhance awareness of risk posed by environmental risk factors and highlight approaches for risk intervention.

Development of an explainable prediction model for the risk of moderate-to-severe obstructive sleep apnea in children.

European journal of pediatrics
UNLABELLED: Early identification of children at high risk for moderate-to-severe obstructive sleep apnea (OSA) is crucial for timely intervention, yet is often hindered by limited access to polysomnography (PSG). We aimed to develop an interpretable ...

Machine Learning Analysis of Retrospective Data From 503 Hospitalized Older Patients With Type 2 Diabetes to Identify Factors Associated With Cognitive Impairment.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Diabetes is increasingly prevalent among older adults; mild cognitive impairment (MCI) comorbidity in this group represents a major concern. Existing MCI prediction methods are often inaccurate, but machine learning (ML) offers improved po...

Machine learning-based integration of tumor deposit molecular signatures improves prognostic stratification in colon adenocarcinoma.

International journal of colorectal disease
BACKGROUND: Colon adenocarcinoma (COAD) remains a leading cause of cancer-related mortality worldwide. Although tumor deposits (TDs) are established prognostic indicators, their molecular characteristics and potential for improving risk stratificatio...

Sex-specific machine learning models for carotid plaque prediction in individuals with fatty liver disease: a cross-sectional study.

BMJ open
INTRODUCTION: Early detection of carotid plaque prevents stroke and myocardial infarction. Individuals with fatty liver might be at an increased risk of developing carotid plaque, yet limited access to carotid artery ultrasound underscores the need f...