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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 PDFDeep learning classification of MGMT status of glioblastomas using multiparametric MRI with a novel domain knowledge augmented mask fusion approach.
Sci Rep
January 2025
Department of Electrical Electronical Engineering, Yaşar University, Bornova, İzmir, Turkey.
We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparametric MRI. We focused on multi-habitat deep image descriptors as our basic focus. A subset of the BRATS 2021 MGMT methylation dataset containing both MGMT class labels and segmentation masks was used.
View Article and Find Full Text PDFAdditional value of fetal magnetic resonance imaging for prenatal diagnosis: A retrospective study.
Eur J Obstet Gynecol Reprod Biol
January 2025
Obstetrics and Fetal Medicine Unit, CHRU of Nancy, Nancy, France; Department of Fetopathology and Placental Pathology, CHRU of Nancy, Nancy, France; Inserm, Diagnostic and Interventional Adaptive Imaging, University of Lorraine, Nancy, France. Electronic address:
Objective: This study aimed to evaluate the utility of fetal MRI in prenatal diagnosis.
Methods: A retrospective study was conducted, including all pregnant women who underwent fetal MRI at a single French university center from 2018 to 2022. Fetal MRI findings were deemed "concordant" if they matched the ultrasound diagnosis.
Usefulness of urinary biomarker-based risk score and multiparametric MRI for clinically significant prostate cancer detection in biopsy-naïve patients.
Abdom Radiol (NY)
January 2025
Departmet of Urology, Medical Academy, Lithuanian University of Health Sciences, Mickeviciaus str. 9, Kaunas, 44307, Lithuania.
Objectives: This study aimed to investigate the accuracy of multiparametric magnetic resonance imaging (mpMRI), genetic urinary test (GUT), and prostate cancer prevention trial risk calculator version 2.0 (PCPTRC2) for the clinically significant prostate cancer (csPCa) diagnostic in biopsy-naïve patients.
Materials And Methods: In a single center study between 2021 and 2024 participants underwent prostate mpMRI, GUT, and ultrasound (US) guided biopsy.
Changes in the Parietal Lobe Subregion Volume at Various Stages of Alzheimer's Disease and the Role in Cognitively Normal and Mild Cognitive Impairment Conversion.
J Integr Neurosci
January 2025
Department of Radiology, Affiliated Hospital of North Sichuan Medical College, 637000 Nanchong, Sichuan, China.
Background: Volume alterations in the parietal subregion have received less attention in Alzheimer's disease (AD), and their role in predicting conversion of mild cognitive impairment (MCI) to AD and cognitively normal (CN) to MCI remains unclear. In this study, we aimed to assess the volumetric variation of the parietal subregion at different cognitive stages in AD and to determine the role of parietal subregions in CN and MCI conversion.
Methods: We included 662 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, including 228 CN, 221 early MCI (EMCI), 112 late MCI (LMCI), and 101 AD participants.
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