PURPOSE: Accurate differentiation of benign renal lesions from renal cell carcinoma (RCC) is crucial for optimized management, particularly for small renal lesions (≤4 cm in diameter). This study aimed to integrate clinical data, radiomic features, a...
BACKGROUND: Chronic kidney disease (CKD) is a prevalent condition with significant global health implications. Early detection and management are critical to prevent disease progression and complications. Deep learning (DL) models using retinal image...
BACKGROUND: Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. Machine learning (ML) systems can enhance DR in community-based screening. However, predictive power models for usability and performance are still being d...
Journal of health, population, and nutrition
Feb 7, 2025
BACKGROUND: Diabetes mellitus, an endocrine system disease, is a common disease involving many patients worldwide. Many studies are performed to evaluate the correlation between micronutrients/macronutrients on diabetes but few of them have a high st...
OBJECTIVE: To explore the early efficacy of an artificial intelligence preoperative planning system (AIHIP system) for assisting in hip revision surgery.
BMC medical informatics and decision making
Feb 7, 2025
BACKGROUND: Low birth weight (LBW) is a critical global health issue that affects infants disproportionately, particularly in developing countries. This study adopted causal machine learning (CML) algorithms for predicting LBW in newborns, drawing fr...
BACKGROUND: Gastric cancer patients are prone to lower extremity deep vein thrombosis (DVT) after surgery, which is an important cause of death in postoperative patients. Therefore, it is particularly important to find a suitable way to predict the r...
The objective was to use convolutional neural networks (CNNs) for automatic segmentation of hip cartilage and labrum based on 3D MRI. In this retrospective single-center study, CNNs with a U-Net architecture were used to develop a fully automated seg...
BACKGROUND: The increasing deployment of conversational artificial intelligence (AI) in mental health interventions necessitates an evaluation of their efficacy in rectifying cognitive biases and recognizing affect in human-AI interactions. These bia...
PURPOSE: To evaluate ChatGPT's ability to analyze comprehensive case descriptions of patients with uveal melanoma and provide recommendations for the most appropriate management.
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