PURPOSE: To assess the added value of artificial intelligence (AI) for radiologists and emergency physicians in the radiographic detection of pelvic fractures.
BACKGROUND: To evaluate the effectiveness of machine learning (ML) techniques in predicting negative remodeling in uncomplicated Stanford type B intramural hematoma (IMHB) during the acute phase.
BACKGROUND: Unplanned readmissions increase unnecessary health care costs and reduce the quality of care. It is essential to plan the discharge care from the beginning of hospitalization to reduce the risk of readmission. Machine learning-based readm...
Hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) is a major contributor to mortality. We developed a recurrence prediction system for HCC patients before and after LT. Data from patients with HCC who underwent LT were retros...
BACKGROUND: The incidence of delirium in patients with burns receiving treatment in the intensive care unit (ICU) is high, reaching up to 77%, and has been associated with increased mortality rates. Therefore, early identification of patients at high...
PURPOSE: To comprehensively analyze the association between preoperative maximum standardized uptake value (SUV) on 18F-fluorodeoxyglucose positron emission tomography-computed tomography and postoperative recurrence in resected non-small cell lung c...
The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation
Mar 4, 2025
BACKGROUND: Cell-free DNA (cfDNA) in ex-vivo lung perfusion (EVLP) perfusate has been shown to potentially reflect lung injury; however, the relationship between cfDNA concentration with clinical EVLP lung outcomes has not been elucidated.
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Mar 4, 2025
OBJECTIVE: To investigate high-risk factors for gestational diabetes mellitus (GDM) in early pregnancy through an analysis of demographic and clinical data, and to develops a machine-learning-based prediction model to enhance early diagnosis and inte...
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