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In the medical field, endoscopic video analysis is crucial for disease diagnosis and minimally invasive surgery. The Endoscopic Foundation Models (Endo- FM) utilize large-scale self-supervised pre-training on endoscopic video data and leverage video transformer models to capture long-range spatiotemporal dependencies. However, detecting complex lesions such as gastrointestinal metaplasia (GIM) in endoscopic videos remains challenging due to unclear boundaries and indistinct features, and Endo-FM has not demonstrated good performance.

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Background: Congenital heart disease (CHD) is a birth defect of the heart that requires long-term care and often leads to additional health complications. Effective educational strategies are essential for improving health literacy and care outcomes. Despite affecting around 40,000 children annually in the United States, there is a gap in understanding children's health literacy, parental educational burdens, and the efficiency of health care providers in delivering education.

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Background: An effective primary treatment for obsessive-compulsive disorder (OCD) in children and adolescents as well as adults is exposure and response prevention (ERP), a form of intervention in the context of cognitive-behavioral therapy. Despite strong evidence supporting the efficacy and effectiveness of ERP from studies in research and real-world settings, its clinical use remains limited. This underuse is often attributed to access barriers such as the scarcity of properly trained therapists, geographical constraints, and costs.

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Enhancing Diagnostic Accuracy of Lung Nodules in Chest Computed Tomography Using Artificial Intelligence: Retrospective Analysis.

J Med Internet Res

January 2025

Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.

Background: Uncertainty in the diagnosis of lung nodules is a challenge for both patients and physicians. Artificial intelligence (AI) systems are increasingly being integrated into medical imaging to assist diagnostic procedures. However, the accuracy of AI systems in identifying and measuring lung nodules on chest computed tomography (CT) scans remains unclear, which requires further evaluation.

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Background: Septic arthritis of the lumbar facet joint (SALFJ) is a rare condition that can lead to serious complications. The authors present an uncommon case in which SALFJ resulted in bacterial meningitis (BM) with hydrocephalus and pyogenic ventriculitis, causing a disturbance of consciousness. Reports describing perforation of the dura mater by an epidural abscess are rare, and the present case offers valuable insights into the management of complex and severe complications arising from SALFJ.

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