Results 121 to 130 of about 137,842 (266)

Performance of ChatGPT and Bard on the medical licensing examinations varies across different cultures: a comparison study

BMC Medical Education
Background This study aimed to evaluate the performance of GPT-3.5, GPT-4, GPT-4o and Google Bard on the United States Medical Licensing Examination (USMLE), the Professional and Linguistic Assessments Board (PLAB), the Hong Kong Medical Licensing ...
Yikai Chen, Xiujie Huang, Fangjie Yang, Haiming Lin, Haoyu Lin, Zhuoqun Zheng, Qifeng Liang, Jinhai Zhang, Xinxin Li   +8 more
doaj   +1 more source

Generative pretrained transformer 4: an innovative approach to facilitate value-based healthcare

Intelligent Medicine
Objective: Appropriate medical imaging is important for value-based care. We aim to evaluate the performance of generative pretrained transformer 4 (GPT-4), an innovative natural language processing model, providing appropriate medical imaging ...
Han Lyu, Zhixiang Wang, Jia Li, Jing Sun, Xinghao Wang, Pengling Ren, Linkun Cai, Zhenchang Wang, Max Wintermark   +8 more
doaj   +1 more source

NMT-GPT

Norsk medietidsskrift, 2023
Nina Kvalheim, Erik Knudsen
openaire   +2 more sources

Optimizing Natural Language Processing: A Comparative Analysis of GPT-3.5, GPT-4, and GPT-4o

Data and Metadata
In the last decade, the advancement of artificial intelligence has transformed multiple sectors, with natural language processing standing out as one of the most dynamic and promising areas. This study focused on comparing the GPT-3.5, GPT-4 and GPT-4o language models, evaluating their efficiency and performance in Natural Language Processing tasks ...
Manuel Ayala-Chauvin, Fátima Avilés-Castillo   +1 more
openaire   +1 more source

Single layer tiny Co4 outpaces GPT-2 and GPT-BERT

Proceedings of the First BabyLM Workshop
We show that a tiny Co$^4$ machine(Adeel,2025) with a single layer, two heads, and 8M parameters, operating at an approximate cost of $O(N)$ (where $N$ is the number of input tokens), outpaces the BabyLM Challenge baselines GPT-2 (124M, 12 layers, $O(N^2))$ and GPT-BERT (30M, 12 layers, $O(N^2))$ in just two epochs, while both are trained for ten.
Zain, Noor Ul, Raza, Mohsin, Adeel, Ahsan   +2 more
openaire   +2 more sources

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Advanced Intelligent Discovery, EarlyView.
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing, He Wang, Yangyang Sun, Xiaoquan Su, Shunyao Wu   +4 more
wiley   +1 more source

ChatGPT With GPT-4 Outperforms Emergency Department Physicians in Diagnostic Accuracy: Retrospective Analysis

Journal of Medical Internet Research
BackgroundOpenAI’s ChatGPT is a pioneering artificial intelligence (AI) in the field of natural language processing, and it holds significant potential in medicine for providing treatment advice.
John Michael Hoppe, Matthias K Auer, Anna Strüven, Steffen Massberg, Christopher Stremmel   +4 more
doaj   +1 more source

Assessing Generative Pretrained Transformers (GPT) in Clinical Decision-Making: Comparative Analysis of GPT-3.5 and GPT-4

Journal of Medical Internet Research
Background Artificial intelligence, particularly chatbot systems, is becoming an instrumental tool in health care, aiding clinical decision-making and patient engagement. Objective This study aims to analyze the performance of ChatGPT ...
Adi Lahat, Kassem Sharif, Narmin Zoabi, Yonatan Shneor Patt, Yousra Sharif, Lior Fisher, Uria Shani, Mohamad Arow, Roni Levin, Eyal Klang   +9 more
openaire   +3 more sources

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Performance of GPT-4o combined with retrieval-augmented generation on nutritionist licensing exam questions

Endocrine Journal
GPT-4o, a general-purpose large language model, has a Retrieval-Augmented Variant (GPT-4o-RAG) that can assist in dietary counseling. However, research on its application in this field remains lacking.
Yu Ishikawa, Akitaka Higashi, Nozomu Arai, Daisuke Ozo, Wataru Hasegawa, Tetsuya Imamura, Zenbei Matsumoto, Hidetaka Nambo, Shigehiro Karashima   +8 more
doaj   +1 more source