BACKGROUND: Body weight unloaded treadmill training has shown limited efficacy in further improving functional capacity after subacute rehabilitation of ischemic stroke patients. Dynamic robot assisted bodyweight unloading is a novel technology that ...
BACKGROUND: Our investigation aimed to determine how the diverse backgrounds and medical specialties of emergency physicians (Eps) influence the accuracy of diagnoses and the subsequent treatment pathways for patients presenting preclinically with MI...
OBJECTIVE: Total hip arthroplasty (THA) remains the primary treatment option for femoral neck fractures in elderly patients. This study aims to explore the risk factors associated with allogeneic blood transfusion after surgery and to develop a dynam...
IMPORTANCE: Machine learning has potential to transform cancer care by helping clinicians prioritize patients for serious illness conversations. However, models need to be evaluated for unequal performance across racial groups (ie, racial bias) so th...
International journal of biological sciences
Jul 1, 2024
Renal cell carcinoma (RCC) is frequently accompanied by tumor thrombus in the venous system with an extremely dismal prognosis. The current Tumor Node Metastasis (TNM) stage and Mayo clinical classification do not appropriately identify preference-s...
This study aimed to develop and validate a machine learning (ML) model tailored to the Korean population with type 2 diabetes mellitus (T2DM) to provide a superior method for predicting the development of cardiovascular disease (CVD), a major chronic...
Endometrial cancer (EC) has four molecular subtypes with strong prognostic value and therapeutic implications. The most common subtype (NSMP; No Specific Molecular Profile) is assigned after exclusion of the defining features of the other three molec...
BACKGROUND: Robust predictive models of clinical impairment and worsening in multiple sclerosis (MS) are needed to identify patients at risk and optimize treatment strategies.
BACKGROUND: Steatotic liver disease (SLD) is a growing phenomenon, and our understanding of its determinants has been limited by our ability to identify it clinically. Natural language processing (NLP) can potentially identify hepatic steatosis syste...