Revisiting the need for the use of GPT in surgery and medicine

Ray, Partha Pratim

doi:10.1007/s10151-023-02847-6

Cited by 1 publication

(2 citation statements)

References 6 publications

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“…Effective data protection is crucial in order to prevent traceability back to individual patients, thereby avoiding breaches that could lead to identity theft or other misuses of medical information [6,32,64]. Such breaches could result in physical, emotional, or financial damages, violating both the privacy and safety of patients [36,54,[65][66][67]. While valid concerns about patient privacy and data security arise when patients share personal information or when conversational agents access patient data, these concerns are not exclusive to LLMs and apply more broadly to electronic patient record systems [32].…”

Section: Patient Privacy and Data Securitymentioning

confidence: 99%

“…When an LLM's advice results in a medical error, leading to an adverse event, who is responsible [38,59,64,68,72]? Is it the developers who created the LLM, the medical professionals who depended on it, or the technology itself [37,67]? Although some sources argue that the physician should take responsibility [35,39,55,73], this ambiguity in assigning responsibility necessitates the establishment of clear guidelines and legal frameworks.…”

Section: Responsibility and Liabilitymentioning

confidence: 99%

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AI and Ethics: A Systematic Review of the Ethical Considerations of Large Language Model Use in Surgery Research

Pressman,

Borna,

Gomez-Cabello

et al. 2024

Healthcare

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Introduction: As large language models receive greater attention in medical research, the investigation of ethical considerations is warranted. This review aims to explore surgery literature to identify ethical concerns surrounding these artificial intelligence models and evaluate how autonomy, beneficence, nonmaleficence, and justice are represented within these ethical discussions to provide insights in order to guide further research and practice. Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Five electronic databases were searched in October 2023. Eligible studies included surgery-related articles that focused on large language models and contained adequate ethical discussion. Study details, including specialty and ethical concerns, were collected. Results: The literature search yielded 1179 articles, with 53 meeting the inclusion criteria. Plastic surgery, orthopedic surgery, and neurosurgery were the most represented surgical specialties. Autonomy was the most explicitly cited ethical principle. The most frequently discussed ethical concern was accuracy (n = 45, 84.9%), followed by bias, patient confidentiality, and responsibility. Conclusion: The ethical implications of using large language models in surgery are complex and evolving. The integration of these models into surgery necessitates continuous ethical discourse to ensure responsible and ethical use, balancing technological advancement with human dignity and safety.

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