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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 PDFA 3D decoupling Alzheimer's disease prediction network based on structural MRI.
Health Inf Sci Syst
December 2025
School of Mathematics and Computing, University of Southern Queensland, 487-535 West Street, Toowoomba, QLD 4350 Australia.
Purpose: This paper aims to develop a three-dimensional (3D) Alzheimer's disease (AD) prediction method, thereby bettering current predictive methods, which struggle to fully harness the potential of structural magnetic resonance imaging (sMRI) data.
Methods: Traditional convolutional neural networks encounter pressing difficulties in accurately focusing on the AD lesion structure. To address this issue, a 3D decoupling, self-attention network for AD prediction is proposed.
Predictors of county-level diabetes-related mortality risks in Florida, USA: a retrospective ecological study.
PeerJ
January 2025
Biomedical and Diagnostic Sciences, University of Tennessee, Knoxville, TN, United States of America.
Background: Diabetes is an increasingly important public health problem due to its socioeconomic impact, high morbidity, and mortality. Although there is evidence of increasing diabetes-related deaths over the last ten years, little is known about the population level predictors of diabetes-related mortality risks (DRMR) in Florida. Identifying these predictors is important for guiding control programs geared at reducing the diabetes burden and improving population health.
View Article and Find Full Text PDFIntroduction: With the introduction of increasingly powerful audio equipment and increase of personal mobile audio devices in the 21st century, the prevalence of noise-induced hearing loss (NIHL) in young adults is expected to increase. This increase, estimated to impact 30 million adults in the next four decades, is due in part to recreational exposure. While many young adults have a general understanding of NIHL, a detailed education on various topics of NIHL could further promote adherence to the use of preventive measures.
View Article and Find Full Text PDFConstruction of Double-layered DNA Tiles and Arrays from Double Crossover Motifs.
Chembiochem
January 2025
State Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, 163 Xianlin Avenue, Nanjing, 210023, P. R. China E-amil.
DNA double crossover (DX) motifs including DAE (double crossover, antiparallel, even spacing) and DAO (double crossover, antiparallel, odd spacing) are well-known monolayered DNA building blocks for construction of 2D DNA arrays and tubes in nanoscale and microscale. Compared to the 3D architectures of DNA origami and single-stranded DNA bricks to build nanoscale 3D bundles, tessellations, gears, castles, etc., designs of double- and multi-layers of DX motifs for 3D architectures are still limited.
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