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Heart-to-heart with ChatGPT: the impact of patients consulting AI for cardiovascular health advice
OBJECTIVES: The advent of conversational artificial intelligence (AI) systems employing large language models such as ChatGPT has sparked public, professional and academic debates on the capabilities of such technologies. This mixed-methods study sets out to review and systematically explore the cap...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10649823/ https://www.ncbi.nlm.nih.gov/pubmed/37945282 http://dx.doi.org/10.1136/openhrt-2023-002455 |
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author | Lautrup, Anton Danholt Hyrup, Tobias Schneider-Kamp, Anna Dahl, Marie Lindholt, Jes Sanddal Schneider-Kamp, Peter |
author_facet | Lautrup, Anton Danholt Hyrup, Tobias Schneider-Kamp, Anna Dahl, Marie Lindholt, Jes Sanddal Schneider-Kamp, Peter |
author_sort | Lautrup, Anton Danholt |
collection | PubMed |
description | OBJECTIVES: The advent of conversational artificial intelligence (AI) systems employing large language models such as ChatGPT has sparked public, professional and academic debates on the capabilities of such technologies. This mixed-methods study sets out to review and systematically explore the capabilities of ChatGPT to adequately provide health advice to patients when prompted regarding four topics from the field of cardiovascular diseases. METHODS: As of 30 May 2023, 528 items on PubMed contained the term ChatGPT in their title and/or abstract, with 258 being classified as journal articles and included in our thematic state-of-the-art review. For the experimental part, we systematically developed and assessed 123 prompts across the four topics based on three classes of users and two languages. Medical and communications experts scored ChatGPT’s responses according to the 4Cs of language model evaluation proposed in this article: correct, concise, comprehensive and comprehensible. RESULTS: The articles reviewed were fairly evenly distributed across discussing how ChatGPT could be used for medical publishing, in clinical practice and for education of medical personnel and/or patients. Quantitatively and qualitatively assessing the capability of ChatGPT on the 123 prompts demonstrated that, while the responses generally received above-average scores, they occupy a spectrum from the concise and correct via the absurd to what only can be described as hazardously incorrect and incomplete. Prompts formulated at higher levels of health literacy generally yielded higher-quality answers. Counterintuitively, responses in a lower-resource language were often of higher quality. CONCLUSIONS: The results emphasise the relationship between prompt and response quality and hint at potentially concerning futures in personalised medicine. The widespread use of large language models for health advice might amplify existing health inequalities and will increase the pressure on healthcare systems by providing easy access to many seemingly likely differential diagnoses and recommendations for seeing a doctor for even harmless ailments. |
format | Online Article Text |
id | pubmed-10649823 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-106498232023-11-09 Heart-to-heart with ChatGPT: the impact of patients consulting AI for cardiovascular health advice Lautrup, Anton Danholt Hyrup, Tobias Schneider-Kamp, Anna Dahl, Marie Lindholt, Jes Sanddal Schneider-Kamp, Peter Open Heart Health Care Delivery, Economics and Global Health Care OBJECTIVES: The advent of conversational artificial intelligence (AI) systems employing large language models such as ChatGPT has sparked public, professional and academic debates on the capabilities of such technologies. This mixed-methods study sets out to review and systematically explore the capabilities of ChatGPT to adequately provide health advice to patients when prompted regarding four topics from the field of cardiovascular diseases. METHODS: As of 30 May 2023, 528 items on PubMed contained the term ChatGPT in their title and/or abstract, with 258 being classified as journal articles and included in our thematic state-of-the-art review. For the experimental part, we systematically developed and assessed 123 prompts across the four topics based on three classes of users and two languages. Medical and communications experts scored ChatGPT’s responses according to the 4Cs of language model evaluation proposed in this article: correct, concise, comprehensive and comprehensible. RESULTS: The articles reviewed were fairly evenly distributed across discussing how ChatGPT could be used for medical publishing, in clinical practice and for education of medical personnel and/or patients. Quantitatively and qualitatively assessing the capability of ChatGPT on the 123 prompts demonstrated that, while the responses generally received above-average scores, they occupy a spectrum from the concise and correct via the absurd to what only can be described as hazardously incorrect and incomplete. Prompts formulated at higher levels of health literacy generally yielded higher-quality answers. Counterintuitively, responses in a lower-resource language were often of higher quality. CONCLUSIONS: The results emphasise the relationship between prompt and response quality and hint at potentially concerning futures in personalised medicine. The widespread use of large language models for health advice might amplify existing health inequalities and will increase the pressure on healthcare systems by providing easy access to many seemingly likely differential diagnoses and recommendations for seeing a doctor for even harmless ailments. BMJ Publishing Group 2023-11-09 /pmc/articles/PMC10649823/ /pubmed/37945282 http://dx.doi.org/10.1136/openhrt-2023-002455 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Health Care Delivery, Economics and Global Health Care Lautrup, Anton Danholt Hyrup, Tobias Schneider-Kamp, Anna Dahl, Marie Lindholt, Jes Sanddal Schneider-Kamp, Peter Heart-to-heart with ChatGPT: the impact of patients consulting AI for cardiovascular health advice |
title | Heart-to-heart with ChatGPT: the impact of patients consulting AI for cardiovascular health advice |
title_full | Heart-to-heart with ChatGPT: the impact of patients consulting AI for cardiovascular health advice |
title_fullStr | Heart-to-heart with ChatGPT: the impact of patients consulting AI for cardiovascular health advice |
title_full_unstemmed | Heart-to-heart with ChatGPT: the impact of patients consulting AI for cardiovascular health advice |
title_short | Heart-to-heart with ChatGPT: the impact of patients consulting AI for cardiovascular health advice |
title_sort | heart-to-heart with chatgpt: the impact of patients consulting ai for cardiovascular health advice |
topic | Health Care Delivery, Economics and Global Health Care |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10649823/ https://www.ncbi.nlm.nih.gov/pubmed/37945282 http://dx.doi.org/10.1136/openhrt-2023-002455 |
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