AIMC Topic: Risk Factors

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Construction and validation of a risk prediction model for complications in patients with acute leukemia based on machine learning.

Scientific reports
Early-phase severe complications remain a major cause of morbidity and mortality during induction chemotherapy for acute leukaemia. Existing risk scores capture only limited prognostic variance and are rarely well-calibrated for clinical decision sup...

Compact machine learning model for perioperative stroke prediction prior to surgery: A retrospective cohort study.

Scientific reports
Perioperative stroke significantly impacts postoperative outcomes. Current risk stratification methods for perioperative stroke prediction lack accuracy and practicality. We aimed to develop a machine learning (ML) model that improves both accuracy a...

Uncovering age-specific subtypes of pediatric obesity and metabolic syndrome using machine learning algorithms.

Scientific reports
Identifying new subgroups among children and adolescents with obesity and metabolic syndrome requires advanced clustering techniques capable of analyzing complex multidimensional data. This study aimed to employ machine learning methods to enhance th...

Machine learning-based management of hypertensive disorders in pregnancy: analysis of differences in key risk factors between gestational hypertension and pre-eclampsia and construction of a pre-eclampsia prediction model.

European journal of medical research
OBJECTIVES: It remains debated whether gestational hypertension (GH) and pre-eclampsia (PE) are distinct entities or different spectra of the same disease. Currently, comparative studies of risk factors for GH and PE in the same population are limite...

Distinct immune-metabolic phenotypes underlie poor coronary collateral circulation.

Cardiovascular diabetology
BACKGROUND: Coronary collateral circulation (CCC) significantly impacts myocardial perfusion and clinical outcomes in coronary artery disease patients, yet the underlying molecular heterogeneity remains inadequately characterized.

XGBoost-based analysis of maternal and biochemical factors associated with spontaneous preterm birth: a retrospective cohort study.

BMC pregnancy and childbirth
BACKGROUND: Spontaneous preterm birth (sPTB) remains a major cause of neonatal morbidity and early risk assessment was poor. This study aimed to evaluate the association and predictive potential of serum biomarkers and maternal factors with sPTB.

C-reactive protein-triglyceride glucose index in predicting three-vessel coronary artery disease risk: a retrospective study using machine learning approaches.

Annals of medicine
BACKGROUND: Three-vessel coronary artery disease (TVD) is a severe subtype of coronary heart disease, strongly associated with inflammation and metabolic dysfunction. The C-reactive protein-triglyceride glucose index (CTI), an integrated measure of i...

Machine learning identification of influencing factors of global Nation-Level hypertension prevalence.

BMC public health
Hypertension remains a critical global public health challenge, with its complex etiology poorly captured by traditional linear models, especially regarding macro-level structural and gender-specific drivers. To address this, we employed an interpret...

Development and internal validation of a preoperative prediction model for postoperative pneumonia in lung cancer patients: a retrospective study.

BMC surgery
PURPOSE: To evaluate the postoperative pneumonia (POP) risk of patients with non-small cell lung cancer (NSCLC), identify influencing factors, develop a LASSO regression-based model to predict POP risk and identify critical influencing factors.

SHAP-based interpretable machine learning for injury risk prediction in university football players: a multi-dimensional data analysis approach.

Scientific reports
Sports injury prediction is crucial for university football player health, yet existing research predominantly focuses on professional athletes and lacks interpretability. Using the Kaggle "University Football Injury Prediction Dataset" (800 Chinese ...