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Cytomorphological diagnosis of sarcoidosis using EBUS-TBNA in a tuberculosis-endemic region.
Rev Esp Patol
January 2025
Department of Pathology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.
Background: Sarcoidosis, a granulomatous inflammatory disease, exhibits diverse clinical manifestations, often affecting multiple organs. Diagnostic challenges arise due to its similarities with tuberculosis, particularly in high-burden areas. Differentiating between the two relies on clinical judgment, laboratory tests, imaging, and invasive procedures.
View Article and Find Full Text PDFThe feasibility of using machine learning to predict COVID-19 cases.
Int J Med Inform
January 2025
School of Geography and the Environment, University of Oxford, South Parks Road, Oxford OX1 3QY, United Kingdom. Electronic address:
Background: Coronavirus Disease 2019 (COVID-19), caused by the SARS-CoV-2 virus, emerged as a global health crisis in 2019, resulting in widespread morbidity and mortality. A persistent challenge during the pandemic has been the accuracy of reported epidemic data, particularly in underdeveloped regions with limited access to COVID-19 test kits and healthcare infrastructure. In the post-COVID era, this issue remains crucial.
View Article and Find Full Text PDFCharacterizing Telehealth Barriers and Preferences to Promote Acceptable Implementation Strategies in Central Uganda: Multilevel Formative Evaluation.
JMIR Form Res
January 2025
Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, United States.
Background: Telehealth approaches can address health care access barriers and improve care delivery in resource-limited settings around the globe. Yet, telehealth adoption in Africa has been limited, due in part to an insufficient understanding of effective strategies for implementation.
Objective: This study aimed to conduct a multi-level formative evaluation identifying barriers and facilitators for implementing telehealth among health service providers and patients in Central Uganda.
Large Language Model Approach for Zero-Shot Information Extraction and Clustering of Japanese Radiology Reports: Algorithm Development and Validation.
JMIR Cancer
January 2025
Division of Radiology and Biomedical Engineering, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Background: The application of natural language processing in medicine has increased significantly, including tasks such as information extraction and classification. Natural language processing plays a crucial role in structuring free-form radiology reports, facilitating the interpretation of textual content, and enhancing data utility through clustering techniques. Clustering allows for the identification of similar lesions and disease patterns across a broad dataset, making it useful for aggregating information and discovering new insights in medical imaging.
View Article and Find Full Text PDFGrading systems and perineural invasion in oral squamous cell carcinoma - a disease-specific survival analysis.
Med Oral Patol Oral Cir Bucal
January 2025
Department of Oral Diagnosis, Piracicaba Dental School University of Campinas, 901, Limeira Avenue Postcode: 13414-903. Piracicaba-SP, Brazil
Background: Oral squamous cell carcinoma (OSCC) is an aggressive cancer, with prognosis influenced by clinical variables as well grading systems and perineural invasion (PNI), which are associated to poorer outcomes, including higher rates of recurrence and metastasis. This study aims to evaluate OSCC using three grading systems and assess the impact of PNI and clinicopathologic parameters on patient survival.
Material And Methods: Eighty-one primary OSCC samples were analyzed.
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