Ann Arbor, April 2, 2024 – When looking for medical information, people can use web search engines or large language models (LLMs) like ChatGPT-4 or Google Bard. However, these artificial intelligence (AI) tools have their limitations and can sometimes generate incorrect advice or instructions. A new study in the American Journal of Preventive Medicine, published by Elsevier, assesses the accuracy and reliability of AI-generated advice against established medical standards and finds that LLMs are not trustworthy enough to replace human medical professionals just yet.
Credit: American Journal of Preventive Medicine
Ann Arbor, April 2, 2024 – When looking for medical information, people can use web search engines or large language models (LLMs) like ChatGPT-4 or Google Bard. However, these artificial intelligence (AI) tools have their limitations and can sometimes generate incorrect advice or instructions. A new study in the American Journal of Preventive Medicine, published by Elsevier, assesses the accuracy and reliability of AI-generated advice against established medical standards and finds that LLMs are not trustworthy enough to replace human medical professionals just yet.
Andrei Brateanu, MD, Department of Internal Medicine, Cleveland Clinic Foundation, says, “Web search engines can provide access to reputable sources of information, offering accurate details on a variety of topics such as preventive measures and general medical questions. Similarly, LLMs can offer medical information that may look very accurate and convincing, when in fact it may be occasionally inaccurate. Therefore, we thought it would be important to compare the answers from LLMs with data obtained from recognized medical organizations. This comparison helps validate the reliability of the medical information by cross-referencing it with trusted healthcare data.”
In the study 56 questions were posed to ChatGPT-4 and Bard, and their responses were evaluated by two physicians for accuracy, with a third resolving any disagreements. Final assessments found 28.6% of ChatGPT-4’s answers accurate, 28.6% inaccurate, and 42.8% partially accurate but incomplete. Bard performed better, with 53.6% of answers accurate, 17.8% inaccurate, and 28.6% partially accurate.
Dr. Brateanu explains, “All LLMs, including ChatGPT-4 and Bard, operate using complex mathematical algorithms. The fact that both models produced responses with inaccuracies or omitted crucial information highlights the ongoing challenge of developing AI tools that can provide dependable medical advice. This might come as a surprise, considering the advanced technology behind these models and their anticipated role in healthcare environments.”
This research underscores the importance of being cautious and critical of medical information obtained from AI sources, reinforcing the need to consult healthcare professionals for accurate medical advice. For healthcare professionals, it points to the potential and limitations of using AI as a supplementary tool in providing patient care and emphasizes the ongoing need for oversight and verification of AI-generated information.
Dr. Brateanu concludes, “AI tools should not be seen as substitutes for medical professionals. Instead, they can be considered as additional resources that, when combined with human expertise, can enhance the overall quality of information provided. As we incorporate AI technology into healthcare, it’s crucial to ensure that the essence of healthcare continues to be fundamentally human.”
Journal
American Journal of Preventive Medicine
DOI
10.1016/j.amepre.2024.02.006
Method of Research
Content analysis
Subject of Research
Not applicable
Article Title
Accuracy of Online Artificial Intelligence Models in Primary Care Settings