Evidence map›Paper›PMID 37566454›Full record

ArticleJournal of medical Internet research2023

Ethical Considerations of Using ChatGPT in Health Care.

Changyu Wang, Siru Liu, Hao Yang, Jiulin Guo, Yuxuan Wu, Jialin Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 194 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
194citing papers in PubMed, 10 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

194 citing papers in PubMed, 10 syntheses or guidelines pooled it.

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  11. Trial
  12. Article
  13. Dr. AI at the tumor board: what did we miss?International urology and nephrology · 2026
    Article
  14. Ethical and responsible use of artificial intelligence in medical education.International journal of emergency medicine · 2026
    Review
  15. Large language models in the vertical integration of spine surgery workflow: a scoping review.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
    Review
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134 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Changyu Wang *Department of Medical Informatics, West China Medical School, Sichuan University, Chengdu, China.ORCID 0000-0003-4548-331X
Siru Liu *Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States.ORCID 0000-0002-5003-5354
Hao YangInformation Center, West China Hospital, Sichuan University, Chengdu, China.ORCID 0000-0002-3505-9403
Jiulin GuoInformation Center, West China Hospital, Sichuan University, Chengdu, China.ORCID 0009-0006-5995-8290
Yuxuan WuDepartment of Medical Informatics, West China Medical School, Sichuan University, Chengdu, China.ORCID 0000-0003-1333-4627
Jialin LiuDepartment of Medical Informatics, West China Medical School, Sichuan University, Chengdu, China.ORCID 0000-0002-1369-4625

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ChatGPT has promising applications in health care, but potential ethical issues need to be addressed proactively to prevent harm. ChatGPT presents potential ethical challenges from legal, humanistic, algorithmic, and informational perspectives. Legal ethics concerns arise from the unclear allocation of responsibility when patient harm occurs and from potential breaches of patient privacy due to data collection. Clear rules and legal boundaries are needed to properly allocate liability and protect users. Humanistic ethics concerns arise from the potential disruption of the physician-patient relationship, humanistic care, and issues of integrity. Overreliance on artificial intelligence (AI) can undermine compassion and erode trust. Transparency and disclosure of AI-generated content are critical to maintaining integrity. Algorithmic ethics raise concerns about algorithmic bias, responsibility, transparency and explainability, as well as validation and evaluation. Information ethics include data bias, validity, and effectiveness. Biased training data can lead to biased output, and overreliance on ChatGPT can reduce patient adherence and encourage self-diagnosis. Ensuring the accuracy, reliability, and validity of ChatGPT-generated content requires rigorous validation and ongoing updates based on clinical practice. To navigate the evolving ethical landscape of AI, AI in health care must adhere to the strictest ethical standards. Through comprehensive ethical guidelines, health care professionals can ensure the responsible use of ChatGPT, promote accurate and reliable information exchange, protect patient privacy, and empower patients to make informed decisions about their health care.

Indexed as

Artificial IntelligenceDisclosureData CollectionHumansPatient ComplianceReproducibility of ResultsAIalgorithmartificial intelligenceartificial intelligence developmentChatGPTdevelopmentethicshealth carelarge language modelspatient privacypatient safetyprivacysafety

Identifiers

PMID37566454
PMCPMC10457697

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.