Assessing AI chatbots efficacy in ophthalmic triage and referrals: A comparative study

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Original Article

Author Details : Sarita Panda, Piyush Jain*, Ankita Mishra, Deepika Priyadarshini, Radhakanta Bhoi

Volume : 10, Issue : 3, Year : 2024

Article Page : 135-139

https://doi.org/10.18231/j.ijooo.2024.026

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Abstract

Aims: To evaluate the efficacy of AI chatbots (OpenAI ChatGPT GPT-3.5, Google Bard, and WebMD) compared to human ophthalmology trainees in triage and referrals for common ophthalmic conditions.
Materials and Methods: A single-center study was conducted at MKCG Medical College, Berhampur, Odisha, involving six ophthalmology trainees. The performance of AI chatbots was assessed based on diagnostic accuracy and triage categorization. Key performance indicators included the accuracy of the top three suggested diagnoses and concordance in recommendations for investigations and referrals.
Results: Physician respondents identified the correct diagnosis among the top three suggestions in 95% of cases. Google Bard achieved 90% accuracy, ChatGPT 85%, and WebMD 20%. High concordance was observed between physician and AI recommendations for investigations and referrals.
Conclusion: AI chatbots demonstrate promising potential in supporting triage and referral decisions for ophthalmic conditions. While human expertise remains crucial, AI tools can augment diagnostic accuracy, improve efficiency, and enhance patient care. Future research should focus on refining AI algorithms, integrating clinical data, and exploring real-world implementation strategies.
 
Keywords: Artificial Intelligence, Ophthalmology, AI Chatbots, Diagnostic Accuracy, Triage, Referrals

How to cite : Panda S, Jain P, Mishra A, Priyadarshini D, Bhoi R, Assessing AI chatbots efficacy in ophthalmic triage and referrals: A comparative study. IP Int J Ocul Oncol Oculoplasty 2024;10(3):135-139

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