Download full-text PDF |
Source |
---|
Asian Pac J Cancer Prev
January 2025
Department of Anatomic Pathology, Faculty of Medicine, Kasralainy, Cairo University, Cairo, Egypt.
Background: Helicobacter pylori bacteria colonize the gastric mucosa and contribute to the occurrence and development of gastrointestinal diseases. According to the WHO, H. pylori bacteria are considered class I carcinogen.
View Article and Find Full Text PDFAnn Surg Oncol
January 2025
Department of Radiology, University of Washington, Seattle, WA, USA.
Background: Ductal carcinoma in situ (DCIS) is overtreated, in part because of inability to predict which DCIS cases diagnosed at core needle biopsy (CNB) will be upstaged at excision. This study aimed to determine whether quantitative magnetic resonance imaging (MRI) features can identify DCIS at risk of upstaging to invasive cancer.
Methods: This prospective observational clinical trial analyzed women with a diagnosis of DCIS on CNB.
Surg Radiol Anat
January 2025
Department of Anatomy, Jagiellonian University Medical College, Mikołaja Kopernika 12, Kraków, 33-332, Poland.
Introduction: The anterior division of the internal iliac artery (ADIIA) is a crucial vascular structure that supplies blood to the pelvic organs, perineum, and gluteal region. The present study demonstrates practical data concerning the anatomy of the ADIIA and its branches. It is hoped that the results of the current study may aid in localizing the pelvic arteries effectively.
View Article and Find Full Text PDFRadiologie (Heidelb)
January 2025
Department of Radiology, Bezmialem Vakıf University, Istanbul, Turkey.
Purpose: To determine whether there is a difference in apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values in white matter pathways in the subacute period after COVID-19 infection and to evaluate the correlation between diffusion tensor imaging (DTI) metrics and laboratory findings.
Material And Methods: The study included 64 healthy controls and 91 patients. Patients were classified as group 1 (all patients, n = 91), group 2 (outpatients, n = 58), or group 3 (inpatients, n = 33).
Radiology
January 2025
From the University of Maryland Medical Intelligent Imaging (UM2ii) Center, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, 22 S Greene St, Baltimore, MD 21201 (C.H.S., A.K., V.P., F.X.D.); Departments of Radiology, Medicine, and Biomedical Data Science, Stanford University, Palo Alto, Calif (C.P.L.); Department of Computer Science and Electrical Engineering, College of Engineering and Information Technology, University of Maryland, Baltimore County, Baltimore, Md (A.J.); Department of Computer Science, University of Maryland, College Park, College Park, Md (H.H.); and University of Maryland Institute for Health Computing, University of Maryland, North Bethesda, Md (H.H., F.X.D.).
Integrating large language models (LLMs) into health care holds substantial potential to enhance clinical workflows and care delivery. However, LLMs also pose serious risks if integration is not thoughtfully executed, with complex challenges spanning accuracy, accessibility, privacy, and regulation. Proprietary commercial LLMs (eg, GPT-4 [OpenAI], Claude 3 Sonnet and Claude 3 Opus [Anthropic], Gemini [Google]) have received much attention from researchers in the medical domain, including radiology.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!