RATIONALE AND OBJECTIVES: To investigate the effect of accelerated deep-learning (DL) multi-b-value DWI (Mb-DWI) on acquisition time, image quality, and predictive ability of microvascular invasion (MVI) in BCLC stage A hepatocellular carcinoma (HCC)...
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
Feb 17, 2025
AIM(S): To determine the correlation between preoperative health education and the emotions of lung cancer patients, artificial intelligence software was used.
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
Feb 17, 2025
BACKGROUND: Gallbladder cancer (GBC) is associated with a poor prognosis. Recurrence patterns and their effect on survival remain ill-defined. This study aimed to analyze recurrence patterns and develop a machine learning (ML) model to predict surviv...
OBJECTIVE: To explore the ability of natural language processing (NLP) methods to identify confounder information beyond what can be identified using claims codes alone for pharmacoepidemiology.
: Diabetes is a rapidly increasing global health challenge compounded by a critical shortage of diabetes care and education specialists. Robot-assisted diabetes care offers a cost-effective and scalable alternative to traditional methods such as trai...
BMC medical informatics and decision making
Feb 17, 2025
BACKGROUND: Depressive disorder, particularly major depressive disorder (MDD), significantly impact individuals and society. Traditional analysis methods often suffer from subjectivity and may not capture complex, non-linear relationships between ris...
BACKGROUND: 18-Fluoro-deoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) is a valuable imaging tool widely used in the management of cancer patients. Deep learning models excel at segmenting highly metabolic tumors but face ch...
BMC medical informatics and decision making
Feb 17, 2025
BACKGROUND: Identifying key variables is essential for developing clinical outcome prediction models based on high-dimensional electronic medical records (EMR). However, despite the abundance of feature selection (FS) methods available, challenges re...
BACKGROUND: Effective management of patients with borderline ovarian tumor (BOT) requires the timely identification of those at a higher risk of recurrence. Artificial neural networks have been successfully used in many areas of clinical event predic...
BACKGROUND: Tuberculosis (TB) continues to pose a significant threat to global public health. Enhancing patient prognosis is essential for alleviating the disease burden.
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