Quantum leap in medical mentorship: exploring ChatGPT’s transition from textbooks to terabytes

ChatGPT, an advanced AI language model, presents a transformative opportunity in several fields including the medical education. This article examines the integration of ChatGPT into healthcare learning environments, exploring its potential to revolutionize knowledge acquisition, personalize educati...

Full description

Saved in:
Bibliographic Details
Main Authors: Santosh Chokkakula, Siomui Chong, Bing Yang, Hong Jiang, Juan Yu, Ruiqin Han, Idress Hamad Attitalla, Chengliang Yin, Shuyao Zhang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Medicine
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1517981/full
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850173317969870848
author Santosh Chokkakula
Siomui Chong
Siomui Chong
Siomui Chong
Bing Yang
Bing Yang
Hong Jiang
Juan Yu
Ruiqin Han
Idress Hamad Attitalla
Chengliang Yin
Shuyao Zhang
author_facet Santosh Chokkakula
Siomui Chong
Siomui Chong
Siomui Chong
Bing Yang
Bing Yang
Hong Jiang
Juan Yu
Ruiqin Han
Idress Hamad Attitalla
Chengliang Yin
Shuyao Zhang
author_sort Santosh Chokkakula
collection DOAJ
description ChatGPT, an advanced AI language model, presents a transformative opportunity in several fields including the medical education. This article examines the integration of ChatGPT into healthcare learning environments, exploring its potential to revolutionize knowledge acquisition, personalize education, support curriculum development, and enhance clinical reasoning. The AI’s ability to swiftly access and synthesize medical information across various specialties offers significant value to students and professionals alike. It provides rapid answers to queries on medical theories, treatment guidelines, and diagnostic methods, potentially accelerating the learning curve. The paper emphasizes the necessity of verifying ChatGPT’s outputs against authoritative medical sources. A key advantage highlighted is the AI’s capacity to tailor learning experiences by assessing individual needs, accommodating diverse learning styles, and offering personalized feedback. The article also considers ChatGPT’s role in shaping curricula and assessment techniques, suggesting that educators may need to adapt their methods to incorporate AI-driven learning tools. Additionally, it explores how ChatGPT could bolster clinical problem-solving through AI-powered simulations, fostering critical thinking and diagnostic acumen among students. While recognizing ChatGPT’s transformative potential in medical education, the article stresses the importance of thoughtful implementation, continuous validation, and the establishment of protocols to ensure its responsible and effective application in healthcare education settings.
format Article
id doaj-art-acedf4e3662a4089bd7e86234f7fbe65
institution OA Journals
issn 2296-858X
language English
publishDate 2025-04-01
publisher Frontiers Media S.A.
record_format Article
series Frontiers in Medicine
spelling doaj-art-acedf4e3662a4089bd7e86234f7fbe652025-08-20T02:19:53ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2025-04-011210.3389/fmed.2025.15179811517981Quantum leap in medical mentorship: exploring ChatGPT’s transition from textbooks to terabytesSantosh Chokkakula0Siomui Chong1Siomui Chong2Siomui Chong3Bing Yang4Bing Yang5Hong Jiang6Juan Yu7Ruiqin Han8Idress Hamad Attitalla9Chengliang Yin10Shuyao Zhang11Department of Microbiology, Chungbuk National University College of Medicine and Medical Research Institute, Cheongju, Chungbuk, Republic of KoreaDepartment of Dermatology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, ChinaDepartment of Dermatology, The First Affiliated Hospital of Jinan University andJinan University Institute of Dermatology, Guangzhou, Guangdong, ChinaInstitute of Collaborative Innovation, University of Macau, Macao SAR, ChinaDepartment of Cell Biology, College of Basic Medical Sciences, Tianjin Medical University, Tianjin, ChinaDepartment of Public Health, International School, Krirk University, Bangkok, ThailandStatistical Office, Department of Operations, Zhuhai People's Hospital, Zhuhai Clinical Medical College of Jinan University, Zhuhai, ChinaDepartment of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, Shenzhen, ChinaState Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China0Department of Microbiology, Faculty of Science, Omar Al-Mukhtar University, AL-Bayda, Libya1Medical Innovation Research Department, Chinese PLA General Hospital, Beijing, China2Department of Pharmacy, Guangzhou Red Cross Hospital of Jinan University, Guangzhou, ChinaChatGPT, an advanced AI language model, presents a transformative opportunity in several fields including the medical education. This article examines the integration of ChatGPT into healthcare learning environments, exploring its potential to revolutionize knowledge acquisition, personalize education, support curriculum development, and enhance clinical reasoning. The AI’s ability to swiftly access and synthesize medical information across various specialties offers significant value to students and professionals alike. It provides rapid answers to queries on medical theories, treatment guidelines, and diagnostic methods, potentially accelerating the learning curve. The paper emphasizes the necessity of verifying ChatGPT’s outputs against authoritative medical sources. A key advantage highlighted is the AI’s capacity to tailor learning experiences by assessing individual needs, accommodating diverse learning styles, and offering personalized feedback. The article also considers ChatGPT’s role in shaping curricula and assessment techniques, suggesting that educators may need to adapt their methods to incorporate AI-driven learning tools. Additionally, it explores how ChatGPT could bolster clinical problem-solving through AI-powered simulations, fostering critical thinking and diagnostic acumen among students. While recognizing ChatGPT’s transformative potential in medical education, the article stresses the importance of thoughtful implementation, continuous validation, and the establishment of protocols to ensure its responsible and effective application in healthcare education settings.https://www.frontiersin.org/articles/10.3389/fmed.2025.1517981/fullartificial intelligenceChatGPTevidence-based medicinehealthcare technologypersonalized learningclinical problem-solving
spellingShingle Santosh Chokkakula
Siomui Chong
Siomui Chong
Siomui Chong
Bing Yang
Bing Yang
Hong Jiang
Juan Yu
Ruiqin Han
Idress Hamad Attitalla
Chengliang Yin
Shuyao Zhang
Quantum leap in medical mentorship: exploring ChatGPT’s transition from textbooks to terabytes
Frontiers in Medicine
artificial intelligence
ChatGPT
evidence-based medicine
healthcare technology
personalized learning
clinical problem-solving
title Quantum leap in medical mentorship: exploring ChatGPT’s transition from textbooks to terabytes
title_full Quantum leap in medical mentorship: exploring ChatGPT’s transition from textbooks to terabytes
title_fullStr Quantum leap in medical mentorship: exploring ChatGPT’s transition from textbooks to terabytes
title_full_unstemmed Quantum leap in medical mentorship: exploring ChatGPT’s transition from textbooks to terabytes
title_short Quantum leap in medical mentorship: exploring ChatGPT’s transition from textbooks to terabytes
title_sort quantum leap in medical mentorship exploring chatgpt s transition from textbooks to terabytes
topic artificial intelligence
ChatGPT
evidence-based medicine
healthcare technology
personalized learning
clinical problem-solving
url https://www.frontiersin.org/articles/10.3389/fmed.2025.1517981/full
work_keys_str_mv AT santoshchokkakula quantumleapinmedicalmentorshipexploringchatgptstransitionfromtextbookstoterabytes
AT siomuichong quantumleapinmedicalmentorshipexploringchatgptstransitionfromtextbookstoterabytes
AT siomuichong quantumleapinmedicalmentorshipexploringchatgptstransitionfromtextbookstoterabytes
AT siomuichong quantumleapinmedicalmentorshipexploringchatgptstransitionfromtextbookstoterabytes
AT bingyang quantumleapinmedicalmentorshipexploringchatgptstransitionfromtextbookstoterabytes
AT bingyang quantumleapinmedicalmentorshipexploringchatgptstransitionfromtextbookstoterabytes
AT hongjiang quantumleapinmedicalmentorshipexploringchatgptstransitionfromtextbookstoterabytes
AT juanyu quantumleapinmedicalmentorshipexploringchatgptstransitionfromtextbookstoterabytes
AT ruiqinhan quantumleapinmedicalmentorshipexploringchatgptstransitionfromtextbookstoterabytes
AT idresshamadattitalla quantumleapinmedicalmentorshipexploringchatgptstransitionfromtextbookstoterabytes
AT chengliangyin quantumleapinmedicalmentorshipexploringchatgptstransitionfromtextbookstoterabytes
AT shuyaozhang quantumleapinmedicalmentorshipexploringchatgptstransitionfromtextbookstoterabytes