The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
ChatGPT in action: Harnessing artificial intelligence potential and addressing ethical challenges in medicine, education, and scientific research
Open accessAbstract
The documentation of psychological trauma is obviously a challenge to clinicians while they are diving deep into remote events related to their clients or patients. The potential role of psychological trauma in the early developmental stages, and even the existence of adverse childhood experiences, is important to prove, yet it is difficult to do so. A diverse range of methods have been applied, all of which presumably benchmark a big therapeutic step; however, these enthusiastic methods frequently do not last for long. While hypnosis supporters, Freudian and Neo-Freudian disciples can be acute enough to enhance and uncover suppressed memories, modern psychiatry relies mostly on diversely structured interviews. Functional magnetic resonance and its related subtleties might help, but the questions that remain unanswered are numerous and confusing. Connecting early experiences with long-term memory while identifying psychological trauma its importance for the individual’s growth trajectory; thus, it remains an intriguing issue.
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“15 publications focused explicitly on this topic [7, 38, 84, 97, 186, 190–199].”
From Artificial intelligence in undergraduate medical education: an updated scoping review (2025) · cites this paper as [192]
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Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., Maningo, J., et al. (2023) · PLOS Digital Health · doi:10.1371/journal.pdig.0000198 · Cited by 4,115
Sallam, M. (2023) · Healthcare · doi:10.3390/healthcare11060887 · Cited by 3,126
GPT-3: Its Nature, Scope, Limits, and Consequences
Floridi, L., & Chiriatti, M. (2020) · Minds and Machines · doi:10.1007/s11023-020-09548-1 · Cited by 2,519
Gilson, A., Safranek, C. W., Huang, T., Socrates, V., Chi, L., Taylor, R. A., & Chartash, D. (2023) · JMIR Medical Education · doi:10.2196/45312 · Cited by 2,078
ChatGPT: five priorities for research
van Dis, E. A. M., Bollen, J., Zuidema, W., van Rooij, R., & Bockting, C. L. (2023) · Nature · doi:10.1038/d41586-023-00288-7 · Cited by 1,842
ChatGPT is fun, but not an author
Thorp, H. H. (2023) · Science · doi:10.1126/science.adg7879 · Cited by 1,437
ChatGPT listed as author on research papers: many scientists disapprove
Stokel-Walker, C. (2023) · Nature · doi:10.1038/d41586-023-00107-z · Cited by 868
ChatGPT: the future of discharge summaries?
Patel, S. B., & Lam, K. (2023) · The Lancet Digital Health · doi:10.1016/s2589-7500(23)00021-3 · Cited by 728
Abstracts written by ChatGPT fool scientists
Else, H. (2023) · Nature · doi:10.1038/d41586-023-00056-7 · Cited by 611
Tools such as ChatGPT threaten transparent science; here are our ground rules for their use
(2023) · Nature · doi:10.1038/d41586-023-00191-1 · Cited by 605
A Conversation on Artificial Intelligence, Chatbots, and Plagiarism in Higher Education
King, M. R., & chatGPT (2023) · Cellular and Molecular Bioengineering · doi:10.1007/s12195-022-00754-8 · Cited by 602
Generating scholarly content with ChatGPT: Ethical challenges for medical publishing
Liebrenz, M., Schleifer, R., Buadze, A., Bhugra, D., & Smith, A. (2023) · The Lancet Digital Health · doi:10.1016/s2589-7500(23)00019-5 · Cited by 594
Open artificial intelligence platforms in nursing education: Tools for academic progress or abuse?
O’Connor, S., & ChatGPT (2023) · Nurse Education in Practice · doi:10.1016/j.nepr.2022.103537 · Cited by 585
AI bot ChatGPT writes smart essays — should professors worry?
Stokel-Walker, C. (2022) · Nature · doi:10.1038/d41586-022-04397-7 · Cited by 543
Dale, R. (2020) · Natural Language Engineering · doi:10.1017/s1351324920000601 · Cited by 509
Rao, A. S., Kim, J., Kamineni, M., Pang, M., Lie, W., Dreyer, K. J., & Succi, M. D. (2023) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2023.05.003 · Cited by 509
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Taecharungroj, V. (2023) · Big Data and Cognitive Computing · doi:10.3390/bdcc7010035 · Cited by 489
Ethical and social risks of harm from Language Models
Weidinger, L., Mellor, J., Rauh, M., Griffin, C., Uesato, J., Huang, P.-S., Cheng, M., Glaese, M., Balle, B., Kasirzadeh, A., et al. (2021) · arXiv · doi:10.48550/arxiv.2112.04359 · Cited by 477
AI for life: Trends in artificial intelligence for biotechnology
Holzinger, A., Keiblinger, K., Holub, P., Zatloukal, K., & Müller, H. (2023) · New Biotechnology · doi:10.1016/j.nbt.2023.02.001 · Cited by 438
ChatGPT: Evolution or revolution?
Gordijn, B., & Have, H. T. (2023) · Medicine, Health Care and Philosophy · doi:10.1007/s11019-023-10136-0 · Cited by 317
Want To Reduce Labeling Cost? GPT-3 Can Help
Wang, S., Liu, Y., Xu, Y., Zhu, C., & Zeng, M. (2021) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2021.findings-emnlp.354 · Cited by 274
Chatterjee, J., & Dethlefs, N. (2023) · Patterns · doi:10.1016/j.patter.2022.100676 · Cited by 263
Health, T. L. D. (2023) · The Lancet Digital Health · doi:10.1016/s2589-7500(23)00023-7 · Cited by 257
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Can ChatGPT draft a research article? An example of population-level vaccine effectiveness analysis
Macdonald, C., Adeloye, D., Sheikh, A., & Rudan, I. (2023) · Journal of Global Health · doi:10.7189/jogh.13.01003 · Cited by 243
One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC EraPreprint
Zhang, C., Zhang, C., Li, C., Qiao, Y., Zheng, S., Dam, S. K., Zhang, M., Kim, J. U., Kim, S. T., Park, G., et al. (2023) · arXiv (Cornell University) · doi:10.13140/rg.2.2.24789.70883 · Cited by 238
Can ChatGPT pass the life support exams without entering the American heart association course?
Fijačko, N., Gosak, L., Štiglic, G., Picard, C. T., & John Douma, M. (2023) · Resuscitation · doi:10.1016/j.resuscitation.2023.109732 · Cited by 206
Ethical ChatGPT: Concerns, Challenges, and Commandments
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Patent claim generation by fine-tuning OpenAI GPT-2
Lee, J.-S., & Hsiang, J. (2020) · World Patent Information · doi:10.1016/j.wpi.2020.101983 · Cited by 174
Analysis of large-language model versus human performance for genetics questions
Duong, D., & Solomon, B. D. (2023) · doi:10.1101/2023.01.27.23285115 · Cited by 159
Analysis of large-language model versus human performance for genetics questions
Duong, D., & Solomon, B. D. (2024) · European Journal of Human Genetics · doi:10.1038/s41431-023-01396-8 · Cited by 159
One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC EraPreprint
Zhang, C.-N., Zhang, C.-S., Li, C., Qiao, Y., Zheng, S., Dam, S. K., Zhang, M.-C., Kim, J. U., Kim, S., Choi, J., et al. (2023) · arXiv.org · doi:10.48550/arxiv.2304.06488 · Cited by 158
Are ChatGPT and AlphaCode going to replace programmers?
Castelvecchi, D. (2022) · Nature · doi:10.1038/d41586-022-04383-z · Cited by 138
To ChatGPT or not to ChatGPT? The Impact of Artificial Intelligence on Academic Publishing
Curtis, N. C., & ChatGPT (2023) · The Pediatric Infectious Disease Journal · doi:10.1097/inf.0000000000003852 · Cited by 138
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Lubowitz, J. H. (2023) · Arthroscopy · doi:10.1016/j.arthro.2023.01.015 · Cited by 132
Medically Aware GPT-3 as a Data Generator for Medical Dialogue Summarization
Chintagunta, B., Katariya, N., Amatriain, X., & Kannan, A. (2021) · doi:10.18653/v1/2021.nlpmc-1.9 · Cited by 129
A conversation with ChatGPT on the role of computational systems biology in stem cell research
Cahan, P., & Treutlein, B. (2023) · Stem Cell Reports · doi:10.1016/j.stemcr.2022.12.009 · Cited by 125
Nath, S., Marie, A., Ellershaw, S., Korot, E., & Keane, P. A. (2022) · British Journal of Ophthalmology · doi:10.1136/bjophthalmol-2022-321141 · Cited by 118
D'Amico, R. S., White, T. G., Shah, H. A., & Langer, D. J. (2023) · Neurosurgery · doi:10.1227/neu.0000000000002414 · Cited by 118
Initial impressions of ChatGPT for anatomy education
Mogali, S. R. (2024) · Anatomical Sciences Education · doi:10.1002/ase.2261 · Cited by 113
The Radicalization Risks of GPT-3 and Advanced Neural Language Models
McGuffie, K., & Newhouse, A. (2020) · arXiv · doi:10.48550/arxiv.2009.06807 · Cited by 86
Artificial intelligence-assisted psychosis risk screening in adolescents: Practices and challenges
Cao, X., & Liu, X. (2022) · World Journal of Psychiatry · doi:10.5498/wjp.v12.i10.1287 · Cited by 65
The moral authority of ChatGPTPreprint
Krügel, S., Ostermaier, A., & Uhl, M. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2301.07098 · Cited by 54
The Capacity for Moral Self-Correction in Large Language Models
Ganguli, D., Askell, A., Schiefer, N., Liao, T. I., Lukošiūtė, K., Chen, A., Goldie, A., Mirhoseini, A., Olsson, C., Hernandez, D., et al. (2023) · arXiv · doi:10.48550/arxiv.2302.07459 · Cited by 53
Priyanshu, A., Vijay, S., Kumar, A., Naidu, R., & Mireshghallah, F. (2023) · arXiv.org · doi:10.48550/arxiv.2305.15008 · Cited by 40
Huh, S. (2023) · Journal of Educational Evaluation for Health Professions · doi:10.3352/jeehp.2023.20.5 · Cited by 25
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Gandhi, P., & Talwar, V. (2023) · Indian Journal of Medical Sciences · doi:10.25259/ijms_34_2023 · Cited by 20
OpenAI, Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., Almeida, D., Altenschmidt, J., Altman, S., et al. (2023) · arXiv · doi:10.48550/arxiv.2303.08774
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Masalkhi, M., Ong, J., Waisberg, E., & Lee, A. G. (2024) · Eye · doi:10.1038/s41433-024-02958-w · Cited by 130
Miao, J., Thongprayoon, C., Suppadungsuk, S., Garcia Valencia, O. A., Qureshi, F., & Cheungpasitporn, W. (2023) · Clinics and Practice · doi:10.3390/clinpract14010008 · Cited by 111
Pressman, S. M., Borna, S., Gomez-Cabello, C. A., Haider, S. A., Haider, C. R., & Forte, A. J. (2024) · Healthcare · doi:10.3390/healthcare12080825 · Cited by 111
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Miao, J., Thongprayoon, C., Suppadungsuk, S., Krisanapan, P., Radhakrishnan, Y., & Cheungpasitporn, W. (2024) · Medicina · doi:10.3390/medicina60010148 · Cited by 114
Metadata
- Authors
- Jeyaraman, M., Ramasubramanian, S., Balaji, S., Jeyaraman, N., Nallakumarasamy, A., & Sharma, S.
- Affiliations
- Dr. M.G.R. Educational and Research Institute (IN)
- Government Medical College Omandurar (IN)
- All India Institute of Medical Sciences (IN)
- ORCID
- Venue
- World Journal of Methodology
- Publisher
- Baishideng Publishing Group Inc.
- Published
- 2023-09-20
- Volume
- 13
- Issue
- 4
- Pages
- 170-178
- ISSN
- 2222-0682 (ISSN-L)
- PMC
- PMC10523250
- OpenAlex
- W4386855886
- Cited by
- 125
- References
- 46
- Citations by year
- 2026: 26 · 2025: 41 · 2024: 50 · 2023: 7
- FWCI
- 1.46
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by-nc
- Locations
- World Journal of Methodology (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- ChatGPT, large language models, artificial intelligence in healthcare, medical education, radiology reporting, academic integrity, AI-generated content, research ethics, algorithmic bias, privacy, accountability, responsible AI use, AI regulation
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