AIMC Topic: Risk Factors

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Identifying subjective life expectancy risk factors in physically active and inactive middle-aged and older adults using machine learning models.

BMC public health
BACKGROUND: Physical activity is a key focus in the field of public health, and subjective life expectancy is closely associated with individuals' physical and psychological well-being. This study aimed to identify the risk factors for subjective lif...

Predicting carotid plaques in metabolic dysfunction-associated steatotic liver disease using machine learning and SHAP interpretation.

Scientific reports
Cardiovascular disease (CVD) remains the most common cause of death worldwide. Carotid plaque is an indicator of subclinical CVDs. Metabolic dysfunction-associated steatotic liver disease (MASLD) is a risk factor for atherosclerotic CVDs. We aimed to...

Incidence and severity of aortic stenosis according to machine learning predicted risk of atrial fibrillation.

Scientific reports
Atrial fibrillation (AF) and aortic stenosis (AS) are two common progressive conditions affecting older persons that share pathobiological pathways. Early detection of AS is critical for improving outcomes, but no prediction tool exists to inform dec...

Construction and validation of a cross-sectional risk classification model for hypoproteinemia in single-center maintenance hemodialysis patient.

Scientific reports
Hypoproteinemia is a common complication across patients receiving maintenance hemodialysis (MHD). Moreover, it is associated with increased risks of cardiovascular events, infection risk, and mortality. This study aimed to construct a classification...

Prevalence, associated factors, and machine learning-based prediction of depression, anxiety, and stress among university students: a cross-sectional study from Bangladesh.

Journal of health, population, and nutrition
BACKGROUND: Mental health challenges are a growing global public health concern, with university students at elevated risk due to academic and social pressures. Although several studies have exmanined mental health among Bangladeshi students, few hav...

Multimodal deep learning model for prediction of breast cancer recurrence risk and correlation with oncotype DX.

Breast cancer research : BCR
BACKGROUND: Proper stratification of recurrence risk in breast cancer is crucial for guiding treatment decisions. This study aims to predict the recurrence risk of breast cancer patients using a multimodal deep learning model that integrates multiple...

Prediction model for depression risk in middle-aged and elderly patients with metabolic syndrome: a nomogram and interpretable machine learning approach based on CHARLS.

BMC psychiatry
BACKGROUND: Individuals with metabolic syndrome (MetS) are more prone to depression, which is a significant complication impacting quality of life. This research seeks to create and validate predictive models for assessing depression risk in patients...

Machine learning model based on preoperative MRI and clinical data for predicting pancreatic fistula after pancreaticoduodenectomy.

BMC medical imaging
OBJECTIVE: To establish and validate a machine learning model using preoperative multi-sequence MRI radiomic features and clinical data to predict pancreatic fistula after pancreaticoduodenectomy (PD).

Machine learning models for the prediction of COVID-19 prognosis in the primary health care setting.

BMC primary care
BACKGROUND: Establishing risk factors associated with severity and prognosis in the early stages of the disease is important to identify patients who need specialized care. Creating new clinical tools to improve health decisions and outcomes in the p...