RATIONALE AND OBJECTIVES: Traditional radiology management models may face challenges in meeting the growing demand for medical imaging services, potentially related to resource scheduling and workflow coordination. This supply-demand imbalance neces... read more
RATIONALE AND OBJECTIVES: This study evaluates the performance of ChatGPT, a large language model (LLM), in selecting appropriate imaging modalities for breast imaging scenarios using the American College of Radiology (ACR) Appropriateness Criteria (... read more
Journal of Korean Neurosurgical Society
Mar 31, 2026
OBJECTIVE: Prevertebral soft tissue swelling (PSTS) is a significant complication of anterior cervical spine surgery (ACSS) that causes dysphagia, dysphonia, and possibly life-threatening airway obstruction. This study aims to develop and internally ... read more
Pulmonary embolism (PE) is a common and potentially fatal venous thromboembolic disease. Traditional management paradigms, often characterized by insufficient multidisciplinary collaboration, frequently lead to inadequate risk assessment and treatmen... read more
Objective: To evaluate the predictive value of machine learning combined with radiomics for treatment response to lenvatinib combined with transarterial chemoembolization (TACE) in patients with unresectable hepatocellular carcinoma (uHCC). Methods: ... read more
Low- and middle-income countries bear the most significant burden of foodborne diseases, impacting their food and nutrition security, trade, and ultimately economic growth. Recent advances in digitization and artificial intelligence provide new oppor... read more
European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
Mar 31, 2026
UNLABELLED: Machine learning (ML) models have shown promise improving outcome prediction and early risk stratification in paediatric emergency department (ED) triage. This review aims to evaluate the diagnostic performance of ML in predicting hospita... read more
BACKGROUND: Critically ill patients generate large volumes of complex data, creating challenges for timely clinical decision making in intensive care units (ICUs). Artificial intelligence (AI) has emerged as a promising tool for supporting diagnosis,... read more
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