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http://dx.doi.org/10.1016/j.ejvs.2024.06.023 | DOI Listing |
Front Artif Intell
January 2025
Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Introduction: Generating physician letters is a time-consuming task in daily clinical practice.
Methods: This study investigates local fine-tuning of large language models (LLMs), specifically LLaMA models, for physician letter generation in a privacy-preserving manner within the field of radiation oncology.
Results: Our findings demonstrate that base LLaMA models, without fine-tuning, are inadequate for effectively generating physician letters.
Sci Rep
January 2025
Department of Urology, Vanderbilt University Medical Center, Nashville, USA.
Recent advancements of large language models (LLMs) like generative pre-trained transformer 4 (GPT-4) have generated significant interest among the scientific community. Yet, the potential of these models to be utilized in clinical settings remains largely unexplored. In this study, we investigated the abilities of multiple LLMs and traditional machine learning models to analyze emergency department (ED) reports and determine if the corresponding visits were due to symptomatic kidney stones.
View Article and Find Full Text PDFRadiology
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 PDFJ Environ Manage
January 2025
Chongqing Environmental Consulting Co., Ltd., CISDI Group Co., Ltd., Chongqing, China. Electronic address:
To deal with the increasingly severe climate crisis and environmental pollution, China launched a nationwide real-time air quality monitoring program in three batches, a milestone moment in its environmental governance history. Using the time-varying difference-in-differences model, this study explores the synergies of this program across 284 cities from 2009 to 2019. The findings are as follows: (1) With environmental information disclosed, the national air quality monitoring program can reduce the outdoor fine particulate matter concentration by an overall effect of 3.
View Article and Find Full Text PDFPlants (Basel)
January 2025
Escuela de Ingeniería en Agronomía, Campus Tecnológico Local San Carlos, Tecnológico de Costa Rica, Alajuela 22321001, Costa Rica.
The role of a plant root system in resource acquisition is relevant to confront drought events caused by climate change. Accordingly, nursery practices like phosphorous (P) fertilization and root pruning have been shown to modify root architecture; however, their combined benefits require further investigation in Mediterranean species. We evaluated the effect of applied P concentrations (0, 15, 60, and 120 mg L P) with or without chemical (copper) root pruning (WCu, WoCu, respectively) in and on morpho-physiological and root architecture traits.
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