Purpose The purpose of this study was to assess the ability of large language models (LLMs) to comprehend the safety management, protection methods, and proper handling of X-rays according to laws and regulations. We evaluated the performance of GPT-4o (OpenAI, San Francisco, CA, USA) and o1-preview (OpenAI) using questions from the 'Operations Chief of Radiography With X-rays' certification examination in Japan. Methods This study engaged GPT-4o and o1-preview in responding to questions from this Japanese certification examination for 'Operations Chief of Radiography With X-rays'. A total of four sets of exams published from April 2023 to October 2024 were used. The accuracy of each model was evaluated across the subjects, including knowledge about the control of X-rays, relevant laws and regulations, knowledge about the measurement of X-rays, and knowledge about the effects of X-rays on organisms. The results were compared between the two models, excluding graphical questions due to o1-preview's inability to interpret images. Results The overall accuracy rates of GPT-4o and o1-preview ranged from 57.5% to 70.0% and from 71.1% to 86.5%, respectively. The GPT-4o achieved passing accuracy rates in the subjects except for relevant laws and regulations. In contrast, o1-preview met the passing criteria across all four sets, despite graphical questions being excluded from scoring. The accuracy of all questions and relevant laws and regulations in o1-preview were significantly higher than those in GPT-4o (p = 0.03 for all questions and p = 0.03 for relevant laws and regulations, respectively). No significant differences in accuracy were found across the other subjects. Conclusions In the Japanese 'Operations Chief of Radiography With X-rays' certification examination, GPT-4o demonstrated a competent performance in the subjects except for relevant laws and regulations, while o1-preview showed a commendable performance across all subjects. When graphical questions were excluded from scoring, the performance of o1-preview surpassed that of GPT-4o in all questions and relevant laws and regulations.
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http://dx.doi.org/10.7759/cureus.74262 | DOI Listing |
Vet Res
January 2025
Department of Veterinary Sciences, University of Turin, Largo Paolo Braccini 2-5, 10095, Grugliasco, TO, Italy.
Neurofilament light chain (Nf-L) is a biomarker for axonal damage in human neurology but is understudied in cattle. With this study we wanted to determine Nf-L stability at two different storage temperatures and Nf-L levels in healthy cattle and the relationship with age, evaluate whether Nf-L holds diagnostic potential for neurological disorders, and whether an association exists between Nf-L in serum and in cerebrospinal fluid (CSF). To do this, we measured Nf-L levels in CSF and serum samples from 49 healthy and 75 sick cattle.
View Article and Find Full Text PDFSci Rep
January 2025
Changde Hospital, Xiangya School of Medicine, Central South University, Renmin Road 818, Changde, 415000, China.
Adaptive radiotherapy (ART) provides greater benefits than intensity-modulated radiotherapy (IMRT) regarding dosimetric outcomes in patients with cervical cancer. To investigate the clinical benefits of ART, we have collected data from 115 cervical cancer patients who underwent radical radiotherapy at our institution. Fifty-nine patients received a single course of IMRT.
View Article and Find Full Text PDFBMC Immunol
January 2025
Laboratory of Oncology, Medical Research Center, The Second People's Hospital of Changzhou, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, China.
Background: B lymphocytes, essential in cellular immunity as antigen-presenting cells and in humoral immunity as major effector cells, play a crucial role in the antitumor response. Our previous work has shown β-glucan enhanced immunoglobulins (Ig) secretion. But the specific mechanisms of B-cell activation with β-glucan are poorly understood.
View Article and Find Full Text PDFJ Healthc Manag
January 2025
Division of Health Care Delivery Research, Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Jacksonville, Florida.
Goal: While studies have examined quality and health outcomes related to the Centers for Medicare & Medicaid Services' (CMS's) Hospital Value-Based Purchasing (HVBP) Program, a significant gap exists in the literature regarding the relationship between pay-for-performance initiatives and hospital financial performance in the program's Efficiency and Cost Reduction domain. This study examined the association between hospitals' cost inefficiency and participation in the HVBP Program by estimating the probability and magnitude of improvement or achievement in the program's Efficiency and Cost Reduction domain.
Methods: The 2014-2019 Efficiency and Cost Reduction domain data were obtained from CMS and merged with the American Hospital Association's Annual Survey Database.
Background: Prior research has explored the link between health information technology (HIT) and performance of accountable care organizations (ACOs). However, the challenges of HIT use in ACOs for the management of chronic diseases among Medicare beneficiaries remain less examined.
Purpose: Given the high costs of implementing HIT and the occurrence of multiple chronic conditions (MCC) among elderly individuals, it is important to understand the extent to which HIT capabilities enable chronic disease management among the Medicare population.
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