ArticleClinical medicine insights. Endocrinology and diabetes2024
Benefit-Risk Assessment of ChatGPT Applications in the Field of Diabetes and Metabolic Illnesses: A Qualitative Study.
Article in Clinical medicine insights. Endocrinology and diabetes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.
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Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Stakeholder Perspectives on the Integration of AI in Diabetes Care: Systematic Review of Qualitative Studies.Journal of medical Internet research · 2026Pooled it
- Ethical concerns of AI in healthcare: A systematic review of qualitative studies.Nursing ethics · 2026Pooled it
- Integrating ChatGPT to support children and adolescents with diabetes mellitus in South African healthcare: Perspectives of healthcare professionals and academics.African journal of primary health care & family medicine · 2026Article
- Gray-zone decisions in subclinical hypothyroidism: a qualitative analysis of ChatGPT responses.BMC endocrine disorders · 2026Article
- Using Large Language Models for Chronic Disease Management Tasks: Scoping Review.JMIR medical informatics · 2025Article
- Federated multimodal AI for precision-equitable diabetes care.Frontiers in digital health · 2025Review
- Benefit-Risk Assessment of ChatGPT Applications in the Field of Diabetes and Metabolic Illnesses: Correspondence.Clinical medicine insights. Endocrinology and diabetes · 2024Article
- Author Response to Comment on: "Benefit-Risk Assessment of ChatGPT Applications in the Field of Diabetes and Metabolic Illnesses: A Qualitative Study".Clinical medicine insights. Endocrinology and diabetes · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The use of ChatGPT and artificial intelligence (AI) in the management of metabolic and endocrine disorders presents both significant opportunities and notable risks. Objectives: To investigate the benefits and risks associated with the application of ChatGPT in managing diabetes and metabolic illnesses by exploring the perspectives of endocrinologists and diabetologists. Methods and materials: The study employed a qualitative research approach. A semi-structured in-depth interview guide was developed. A convenience sample of 25 endocrinologists and diabetologists was enrolled and interviewed. All interviews were audiotaped and verbatim transcribed; then, thematic analysis was used to determine the themes in the data. Results: The findings of the thematic analysis resulted in 19 codes and 9 major themes regarding the benefits of implementing AI and ChatGPT in managing diabetes and metabolic illnesses. Moreover, the extracted risks of implementing AI and ChatGPT in managing diabetes and metabolic illnesses were categorized into 7 themes and 14 codes. The benefits of heightened diagnostic precision, tailored treatment, and efficient resource utilization have potential to improve patient results. Concurrently, the identification of potential challenges, such as data security concerns and the need for AI that can be explained, enables stakeholders to proactively tackle these issues. Conclusions: Regulatory frameworks must evolve to keep pace with the rapid adoption of AI in healthcare. Sustained attention to ethical considerations, including obtaining patient consent, safeguarding data privacy, ensuring accountability, and promoting fairness, remains critical. Despite its potential impact on the human aspect of healthcare, AI will remain an integral component of patient-centered care. Striking a balance between AI-assisted decision-making and human expertise is essential to uphold trust and provide comprehensive patient care.
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Registered trials
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