Exploring the feasibility of integrating artificial intelligence in pediatric healthcare: a preliminary study with ChatGPT
Explorando la viabilidad de la integración de la inteligencia artificial en la atención médica pediátrica: Un estudio preliminar con ChatGPT
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Objective: To evaluate the accuracy of the ChatGPT model in providing advice to parents with sick or compromised children. Methods: Twelve pediatric doctors assessed their agreement with ChatGPT's responses to fourteen questions about child health using a five-option Likert scale ranging from "strongly disagree" to "strongly agree." Results: The majority of the doctors (over 90%) agreed or strongly agreed with most (12 of 14) of ChatGPT's responses, and in seven of the fourteen responses, more than half of them strongly agreed with the answers. Conclusions: ChatGPT can generate accurate and useful answers for some common pediatric health questions. With further development and validation, it could improve accessibility to appropriate information for pediatric healthcare.
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Haug CJ, Drazen JM. Artificial Intelligence and Machine Learning in Clinical Medicine, 2023. N Engl J Med. 2023;388(13):1201-8. doi:10.1056/NEJMra2302038
Ahuja AS. The impact of artificial intelligence in medicine on the future role of the physician. PeerJ. 2019;7:e7702. doi: 10.7717/peerj.7702
Castelvecchi D. Are ChatGPT and AlphaCode going to replace programmers? Nature. 2022. doi:10.1038/d41586-022-04383z
Introducing ChatGPT [Internet]. [citado el 27 de marzo de 2023]. Disponible en: https://openai.com/blog/chatgpt
Kung TH, Cheatham M, Medenilla A, Sillos C, de Leon L, Elepaño C, et al. Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models. PLOS Digit Health. 2023;2(2):e0000198. doi:10.1371/journal.pdig.0000198
Baumgartner C. The potential impact of ChatGPT in clinical and translational medicine. Clin Transl Med. 2023;13(3):e1206. doi:10.1002/ctm2.1206
Lee DJ, Cronin R, Robinson J, Anders S, Unertl K, Kelly K, et al. Common Consumer Health-Related Needs in the Pediatric Hospital Setting: Lessons from an Engagement Consultation Service. Appl Clin Inform. 2018;9(3):595-603. doi:10.1055/s0038-1667205
Kleinert S. Singapore Statement: a global agreement on responsible research conduct. Lancet. 2010;376(9747):1125-7. doi:10.1016/S0140-6736(10)61456-0
Brown T, Mann B, Ryder N, Subbiah M, Kaplan JD, Dhariwal P, et al. Language Models are Few-Shot Learners. In: Advances in Neural Information Processing Systems [Internet]. Curran Associates, Inc.; 2020 [citado el 28 de marzo de 2023]. p. 1877–901. Disponible en: https://proceedings.neurips.cc/paper/2020/hash/1457c0d6bfcb4967418bfb8ac142f64a-Abstract.html
Biswas SS. Role of Chat GPT in Public Health. Ann Biomed Eng. 2023;51(5):868-9. doi:10.1007/s10439-023-03172-7
Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J. 2019;6(2):94-98. doi:10.7861/ futurehosp.6-2-94
Ayers JW, Poliak A, Dredze M, Leas EC, Zhu Z, Kelley JB, et al. Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum. JAMA Intern Med. 2023:e231838. doi: 10.1001/jamainternmed.2023.1838
Alkaissi H, McFarlane SI. Artificial Hallucinations in ChatGPT: Implications in Scientific Writing. Cureus. 2023;15(2):e35179. doi:10.7759/cureus.35179
