This study aimed to develop and validate machine learning (ML) models to predict the occurrence of delayed hyponatremia after transsphenoidal surgery for pituitary adenoma. We retrospectively collected clinical data on patients with pituitary adenoma...
BACKGROUND: Chronic kidney disease (CKD) imposes a significant global health and economic burden, impacting millions globally. Despite its high prevalence, public awareness and understanding of CKD remain limited, leading to delayed diagnosis and sub...
BACKGROUND: The global prevalence of diabetes has been rising rapidly in recent years, leading to an increase in patients experiencing hyperglycemic crises like diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemic state (HHS). Patients with imp...
Public understanding of medical innovations such as smart technology is decisive for its acceptance and implementation. Thus, it is important to understand what visions people develop of a technology based on initial information such as the label. We...
Self-rated health (SRH) is a significant predictor of future health outcomes. Despite the contribution of psychological factors in individuals' subjective health assessments, prior studies of machine learning-based prediction models primarily focused...
OBJECTIVES: This study compared the characteristics of lesions suspicious for hepatocellular carcinoma (HCC) and their LI-RADS classifications in adaptive statistical iterative reconstruction (ASIR) and deep learning reconstruction (DLR) to those of ...
INTRODUCTION: Understanding 1-year mortality following major surgery offers valuable insights into patient outcomes and the quality of peri-operative care. Few models exist that predict 1-year mortality accurately. This study aimed to develop a predi...
International forum of allergy & rhinology
Jan 8, 2025
BACKGROUND: We developed and assessed the performance of a machine learning model (MLM) to identify, classify, and segment sinonasal masses based on endoscopic appearance.
With the development of deep learning (DL) techniques, there has been a successful application of this approach to determine biological age from latent information contained in retinal images. Retinal age gap (RAG) defined as the difference between c...
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