The international journal of cardiovascular imaging
Sep 25, 2024
Transesophageal echocardiography (TEE) is the standard method for diagnosing left atrial appendage (LAA) hypercoagulability in patients with atrial fibrillation (AF), which means LAA thrombus/sludge, dense spontaneous echo contrast and slow LAA blood...
OBJECTIVES: This study aimed to assess the diagnostic performance of a support vector machine (SVM) algorithm for acute cholecystitis and evaluate its effectiveness in accurately diagnosing this condition.
International journal of chronic obstructive pulmonary disease
Sep 24, 2024
PURPOSE: To employ bioinformatics and machine learning to predict the characteristics of immune cells and genes associated with the inflammatory response and ferroptosis in chronic obstructive pulmonary disease (COPD) patients and to aid in the devel...
OBJECTIVE: Accurate assessment of Fuhrman grade is crucial for optimal clinical management and personalized treatment strategies in patients with clear cell renal cell carcinoma (CCRCC). In this study, we developed a predictive model using ultrasound...
BACKGROUND: We review and analyze research on the application of machine learning (ML) and deep learning (DL) models to lymph node metastasis (LNM) prediction in patients with T1 colorectal cancer (CRC). Predicting LNM before radical surgery is impor...
BACKGROUND: Catheter-related bladder discomfort (CRBD) commonly occurs in patients who have indwelling urinary catheters while under general anesthesia. And moderate-to-severe CRBD can lead to significant adverse events and negatively impact patient ...
The Journal of thoracic and cardiovascular surgery
Sep 18, 2024
OBJECTIVE: The study objective was to develop and validate an interpretable machine learning model to predict 1-year mortality in patients with type A aortic dissection, improving risk classification and aiding clinical decision-making.
BACKGROUND AND PURPOSE: Computed tomography (CT) and biopsy may be insufficient for preoperative evaluation of the grade and outcome of patients with chondrosarcoma. The aim of this study was to develop and validate a CT-based deep learning radiomics...
Hernia : the journal of hernias and abdominal wall surgery
Sep 17, 2024
PURPOSE: This study aimed to develop, validate, and evaluate machine learning (ML) algorithms for predicting Surgical site infections (SSI) and surgical site occurrences (SSO) after elective open inguinal hernia surgery.
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