BACKGROUND: Falls impact over 25% of older adults annually, making fall prevention a critical public health focus. We aimed to develop and validate a machine learning-based prediction model for serious fall-related injuries (FRIs) among community-dwe...
Journal of pediatric gastroenterology and nutrition
Dec 10, 2023
OBJECTIVES: While higher infliximab (IFX) trough concentrations (TCs) are associated with better outcomes in patients with inflammatory bowel disease (IBD), they could pose a risk for adverse events (AEs), including IFX-induced skin lesions. Therefor...
BACKGROUND: Classification of perioperative risk is important for patient care, resource allocation, and guiding shared decision-making. Using discriminative features from the electronic health record (EHR), machine-learning algorithms can create dig...
OBJECTIVE: Preterm birth remains the predominant cause of perinatal mortality throughout the United States and the world, with well-documented racial and socioeconomic disparities. To develop and validate a predictive algorithm for all-cause preterm ...
PURPOSE OF REVIEW: To review current evidence, discuss key knowledge gaps and identify opportunities for development, validation and application of polysocial risk scores (pSRS) for cardiovascular disease (CVD) risk prediction and population cardiova...
Revista do Colegio Brasileiro de Cirurgioes
Dec 1, 2023
INTRODUCTION: the ability of the care team to reliably predict postoperative risk is essential for improvements in surgical decision-making, patient and family counseling, and resource allocation in hospitals. The Artificial Intelligence (AI)-powered...
The Journal of thoracic and cardiovascular surgery
Nov 29, 2023
BACKGROUND: The clinical applicability of machine learning predictions of patient outcomes following cardiac surgery remains unclear. We applied machine learning to predict patient outcomes associated with high morbidity and mortality after cardiac s...
Current risk scores using clinical risk factors for predicting ischemic heart disease (IHD) events-the leading cause of global mortality-have known limitations and may be improved by imaging biomarkers. While body composition (BC) imaging biomarkers ...
BACKGROUND: This study aimed to evaluate the risk factors for machine learning (ML) algorithms in predicting postoperative surgical site infection (SSI) following spine surgery.
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