MediGPT: Exploring Potentials of Conventional and Large Language Models on Medical Data-Reference-Cited by-同舟云学术

MediGPT: Exploring Potentials of Conventional and Large Language Models on Medical Data

Published:2024 Issue: Volume:12 Page:103473-103487
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Abu Tareq Rony Mohammad¹^ORCID,Shariful Islam Mohammad²^ORCID,Sultan Tipu³^ORCID,Alshathri Samah⁴^ORCID,El-Shafai Walid⁵^ORCID

Affiliation:

1. Department of Statistics, Noakhali Science & Technology University, Noakhali, Bangladesh

2. Department of Computer Science and Telecommunication Engineering, Noakhali Science & Technology University, Noakhali, Bangladesh

3. Department of Computer Science, College of Computer and Information Sciences, Fordham University, Bronx, NY, USA

4. Department of Information Technology, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P. O. Box, 84428, Riyadh, Saudi Arabia

5. Computer Science Department, Security Engineering Laboratory, Prince Sultan University, Riyadh, Saudi Arabia

Funder

Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia, through the Researchers Supporting Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10599190.pdf?arnumber=10599190

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3. BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension;Lewis;arXiv:1910.13461,2019

4. Exploring the limits of transfer learning with a unified text-to-text transformer;Raffel;J. Mach. Learn. Res.,2020

5. GPTs are GPTs: An early look at the labor market impact potential of large language models;Eloundou;arXiv:2303.10130,2023

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