AIMC Topic: Risk Factors

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Machine learning-based cardiovascular risk calculator for non-cardiac surgery.

Open heart
BACKGROUND: Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least one cardiovascular risk factor. It is estimated that the 30-day mortality is between 0.5% and 2%.The main objective of this st...

Machine learning for screening laryngopharyngeal reflux symptoms in college students: a cross-sectional study.

Annals of medicine
BCKGROUND: Laryngopharyngeal reflux (LPR) is a widespread global health issue. Its recurring symptoms and impact on quality of life create significant economic burdens for individuals and society. To examine the links between lifestyle, diet, and LPR...

Research Priorities and Future Directions in Cardio-Oncology.

Current treatment options in oncology
The subspecialty of cardio-oncology has undergone significant growth in recent years, alongside major advances in the management of both cardiovascular disease and cancer, the leading causes of morbidity and mortality in the United States and many co...

Factors associated with complication of cranioplasty: CT-based risk assessment for early failure of autologous-bone cranioplasty.

Neurosurgical review
To determine whether preoperative noncontrast CT features predict early revision after autologous bone cranioplasty and to develop a simple CT-based risk framework. We retrospectively studied adults undergoing autologous cranioplasty at a single cent...

How perceived stress and social support shape non-communicable disease risks beyond traditional factors: a machine learning perspective.

BMC public health
BACKGROUND: Psychosocial factors such as perceived stress and social support have been increasingly recognized as significant contributors to non-communicable diseases (NCDs). However, their predictive value in comparison to traditional risk factors ...

Aligning a Household-Level Service Array Through a Jurisdiction-Wide Child Maltreatment Prevention Effort: Protocol for a Geospatial and Counterfactual Modeling Study.

JMIR research protocols
BACKGROUND: Child maltreatment is associated with multiple negative outcomes at the individual and societal levels. Children experiencing maltreatment are at greater risk of a host of negative outcomes (eg, psychological disorders, substance use, vio...

Lymphocytes and related inflammatory factors as predictors of metabolic syndrome risk in shift workers: A machine learning approach based on large-scale population data.

PloS one
BACKGROUND: Metabolic syndrome (MetS) is characterized by chronic inflammation and can be worsened by circadian disruption, which is common among shift work. Machine learning can predict the risk of MetS in shift workers using inflammatory biomarkers...

Cardiovascular Care in Pediatric Cancer Survivors: Updates on Risk, Prevention, and Therapies.

Current treatment options in oncology
Improved survival in pediatric oncology has highlighted the growing burden of cancer treatment-related cardiotoxicity among survivors of childhood cancers. While the cardiotoxicity of anthracyclines and chest radiation are well documented as major co...

Establishment of a postoperative delirium risk prediction model for elderly hip fracture patients based on machine learning algorithms.

BMC geriatrics
BACKGROUND: Although no definitive treatment exists, 30-40% of postoperative delirium cases are preventable through early risk identification and intervention. Therefore our aim was to develop and evaluate a postoperative delirium risk prediction mod...