OBJECTIVE: This study aimed to use machine learning (ML) to establish risk factor and prediction models of osteonecrosis of the femoral head (ONFH) in patients with femoral neck fractures (FNFs) after internal fixation.
BACKGROUND: Cerebral small vessel disease (CSVD) is a major cause of stroke, particularly in the elderly population, leading to significant morbidity and mortality. Accurate identification of high-risk patients and timing of stroke occurrence plays a...
This study aims to develop an ensemble learning (EL) method based on magnetic resonance (MR) radiomic features to preoperatively differentiate intracranial extraventricular ependymoma (IEE) from glioblastoma (GBM). This retrospective study enrolled p...
BACKGROUND: Delayed clinically important postoperative nausea and vomiting (CIPONV) could lead to significant consequences following surgery. We aimed to develop a prediction model for it using machine learning algorithms utilizing perioperative data...
Sarcopenia has been recognized as a determining factor in surgical outcomes and is associated with an increased risk of postoperative complications and readmission. Diagnosis is currently based on clinical guidelines, which includes assessment of sk...
PURPOSE: The purpose of this study was to identify early indicators of keratoconus progression in Pentacam data using machine learning (ML) techniques.
BACKGROUND: Non-Alcoholic Steatohepatitis (NASH) is a crucial stage in the progression of Non-Alcoholic Fatty Liver Disease(NAFLD). The purpose of this study is to explore the clinical value of ultrasound features and radiological analysis in predict...
Journal of clinical monitoring and computing
Aug 19, 2024
PURPOSE: Intraoperative hypotension is associated with adverse outcomes. Predicting and proactively managing hypotension can reduce its incidence. Previously, hypotension prediction algorithms using artificial intelligence were developed for invasive...
BACKGROUND: To construct and evaluate a predictive model for in-hospital mortality among critically ill patients with acute kidney injury (AKI) undergoing continuous renal replacement therapy (CRRT), based on nine machine learning (ML) algorithm.
British journal of hospital medicine (London, England : 2005)
Aug 19, 2024
An artificial intelligence-assisted prediction model for enteral nutrition-associated diarrhoea (ENAD) in acute pancreatitis (AP) was developed utilising data obtained from bowel sounds auscultation. This model underwent validation through a single-...