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Diversity of central nervous system manifestations in Sjogren's Disease: a case-based review.
Rheumatol Int
January 2025
Department of Rheumatology, Clinical Immunology, Geriatrics and Internal Medicine, Medical University of Gdansk, Gdansk, Poland.
Sjogren's disease (SjD) is a chronic and disabling autoimmune disease, predominantly characterized by dryness of the mouth and eyes, resulting from lymphocytic infiltration of exocrine glands. While these are the most prominent symptoms, extra-glandular manifestations are also common. Studies suggest that up to 70% of SjD patients experience neurological symptoms, which interestingly often precede the hallmark dryness.
View Article and Find Full Text PDFAutomated Deep Learning-Based Detection and Segmentation of Lung Tumors at CT.
Radiology
January 2025
Stanford University School of Medicine, Department of Radiation Oncology, Stanford, CA, US.
Background Detection and segmentation of lung tumors on CT scans are critical for monitoring cancer progression, evaluating treatment responses, and planning radiation therapy; however, manual delineation is labor-intensive and subject to physician variability. Purpose To develop and evaluate an ensemble deep learning model for automating identification and segmentation of lung tumors on CT scans. Materials and Methods A retrospective study was conducted between July 2019 and November 2024 using a large dataset of CT simulation scans and clinical lung tumor segmentations from radiotherapy plans.
View Article and Find Full Text PDFMacrotrabecular-Massive Hepatocellular Carcinoma: A Case Report.
Cureus
December 2024
Department of Clinical Immunology and Allergology, Iuliu Hatieganu University of Medicine and Pharmacy of Cluj, Cluj-Napoca, ROU.
Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) is a rare and aggressive molecular subtype of hepatocellular carcinoma (HCC) associated with a poor prognosis. Unlike typical HCC, which commonly arises in the context of cirrhosis, MTM-HCC can develop in non-cirrhotic livers, presenting unique diagnostic and therapeutic challenges. This case report describes a 35-year-old male who presented with persistent epigastric pain, fatigue, and loss of appetite.
View Article and Find Full Text PDFProspective Applications of Artificial Intelligence In Fetal Medicine: A Scoping Review of Recent Updates.
Int J Gen Med
January 2025
Department of Pediatrics, College of Medicine, Arab Gulf University, Al Manama, Bahrain.
Introduction: With the incorporation of artificial intelligence (AI), significant advancements have occurred in the field of fetal medicine, holding the potential to transform prenatal care and diagnostics, promising to revolutionize prenatal care and diagnostics. This scoping review aims to explore the recent updates in the prospective application of AI in fetal medicine, evaluating its current uses, potential benefits, and limitations.
Methods: Compiling literature concerning the utilization of AI in fetal medicine does not appear to modify the subject or provide an exhaustive exploration of electronic databases.
Towards personalized cardiometabolic risk prediction: A fusion of exposome and AI.
Heliyon
January 2025
Center for Applied Intelligent Systems Research, Halmstad University, Sweden.
The influence of the exposome on major health conditions like cardiovascular disease (CVD) is widely recognized. However, integrating diverse exposome factors into predictive models for personalized health assessments remains a challenge due to the complexity and variability of environmental exposures and lifestyle factors. A machine learning (ML) model designed for predicting CVD risk is introduced in this study, relying on easily accessible exposome factors.
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