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Examining the Accuracy and Reproducibility of Responses to Nutrition Questions Related to Inflammatory Bowel Disease by Generative Pre-trained Transformer-4.
Crohns Colitis 360
January 2025
Department of Medicine, Karsh Division of Digestive and Liver Diseases, Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Background: Generative pre-trained transformer-4 (GPT-4) is a large language model (LLM) trained on a vast corpus of data, including the medical literature. Nutrition plays an important role in managing inflammatory bowel disease (IBD), with an unmet need for nutrition-related patient education resources. This study examines the accuracy, comprehensiveness, and reproducibility of responses by GPT-4 to patient nutrition questions related to IBD.
View Article and Find Full Text PDFRecently, foundation models (such as ChatGPT) have emerged with powerful learning, understanding, and generalization abilities, showcasing tremendous potential to revolutionarily promote modern industry. Despite significant advancements in various fields, existing general foundation models face challenges in industry when dealing with the data of specialized modalities, the tasks of varying-scenario with multiple processes, and the requirements of trustworthy output, which makes industrial foundation model (IFM) a necessity. This article proposes a system architecture of termed IFMsys, including model training, model adaptation, and model application.
View Article and Find Full Text PDFIntegration of the SECI model and ChatGPT in higher education.
Heliyon
February 2025
School of Administrative Sciences, Universidad Nacional de San Antonio Abad del Cusco, Cusco, Peru.
In educational settings, the socialization, externalization, combination, and internalization (SECI) model promotes collaboration, the creation of new knowledge, and the integration of individual and collective experiences, thereby enriching learning with greater depth and meaning. The objective of this study was to identify the factors that contribute to the optimal development of the SECI model through the use of ChatGPT, to understand their interaction. The experiment included undergraduate students of business sciences at public and private universities in Cusco, Huancayo, and Lima, Peru.
View Article and Find Full Text PDFThe role of GPT in promoting inclusive higher education for people with various learning disabilities: a review.
PeerJ Comput Sci
February 2025
Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing, Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen, China.
The generative pre-trained transformer (GPT) is a notable breakthrough in the field of artificial intelligence, as it empowers machines to effectively comprehend and engage in interactions with humans. The GPT exhibits the capacity to enhance inclusivity and accessibility for students with learning disabilities in the context of higher education, hence potentially facilitating substantial advancements in the field. GPT can provide personalized and diverse solutions that successfully cater to the distinct requirements of students with learning disabilities.
View Article and Find Full Text PDFAccuracy of Artificial Intelligence Versus Clinicians in Real-Life Case Scenarios of Retinopathy of Prematurity.
Cureus
February 2025
Srimati Kanuri Santhamma Center for Vitreo-Retinal Diseases, Anant Bajaj Retina Institute, Kallam Anji Reddy Campus, L V Prasad Eye Institute, Hyderabad, IND.
Objective The aim of this study was to compare the accuracy of ChatGPT artificial intelligence (AI) with clinicians in real-life case scenarios related to retinopathy of prematurity (ROP). Methods This was a prospectively conducted study with a real-life case scenario-based questionnaire with multiple-response answers. Thirteen clinicians, including eight vitreoretinal fellowship trainees (with less than two years of experience in the management of ROP) and five ROP experts (with more than three years of experience in the management of ROP), were given 10 real-life case scenarios in ROP.
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