ChatGPT in action: Harnessing artificial intelligence potential and addressing ethical challenges in medicine, education, and scientific research
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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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Fifteen publications focused explicitly on ethical considerations concerning the use of AI in medical education.
“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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Chatgpt-Assisted Decision-Making: An In-Depth Exploration of the Human-Ai InteractionPreprint
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Instructions for authors for large language models: Missing in action!
CASSAI, A. D., Dost, B., Mormando, G., Boscolo, A., & Navalesi, P. (2025) · Journal of Clinical Anesthesia · doi:10.1016/j.jclinane.2025.111761
- 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 · 2020: 1
- 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
- Social Sciences › Safety Research › 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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