Exploring the Test-Taking Capabilities of Chatbots—From Surgeon to Sommelier

Chia, Mark A.; Keane, Pearse A.

doi:10.1001/jamaophthalmol.2023.3003

Cited by 5 publications

(2 citation statements)

References 10 publications

(14 reference statements)

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“… 6 , 15 , 16 , 17 Studies that have evaluated AI tools in clinical scenarios often fail to capture the nuances of real-world decision-making, where single best solutions are rare. 18 , 19 Rather, clinical judgments frequently hinge on the principle of what a competent peer would consider a reasonable course of action. 20 To our knowledge, AI tools have not been sufficiently evaluated in such contextual conditions.…”

Section: Introductionmentioning

confidence: 99%

The ability of artificial intelligence tools to formulate orthopaedic clinical decisions in comparison to human clinicians: An analysis of ChatGPT 3.5, ChatGPT 4, and Bard

Agharia,

Szatkowski,

Fraval

et al. 2024

Journal of Orthopaedics

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Section: Introductionmentioning

confidence: 99%

The ability of artificial intelligence tools to formulate orthopaedic clinical decisions in comparison to human clinicians: An analysis of ChatGPT 3.5, ChatGPT 4, and Bard

Agharia,

Szatkowski,

Fraval

et al. 2024

Journal of Orthopaedics

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“…It is essential that users of these tools approach any AI-generated output with caution, as AI systems cannot be held responsible for any mishappenings, as Bressler notes . Furthermore, when using an AI chatbot for learning purposes, it is important to wholistically scrutinize its responses for inaccuracies …”

mentioning

confidence: 99%

Advances in Artificial Intelligence Chatbot Technology in Ophthalmology—Reply

Mihalache,

Popovic,

Muni

2023

JAMA Ophthalmol

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Ethical considerations for large language models in ophthalmology

Kalaw,

Baxter

2024

Current Opinion in Ophthalmology

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Purpose of review This review aims to summarize and discuss the ethical considerations regarding large language model (LLM) use in the field of ophthalmology. Recent findings This review of 47 articles on LLM applications in ophthalmology highlights their diverse potential uses, including education, research, clinical decision support, and surgical assistance (as an aid in operative notes). We also review ethical considerations such as the inability of LLMs to interpret data accurately, the risk of promoting controversial or harmful recommendations, and breaches of data privacy. These concerns imply the need for cautious integration of artificial intelligence in healthcare, emphasizing human oversight, transparency, and accountability to mitigate risks and uphold ethical standards. Summary The integration of LLMs in ophthalmology offers potential advantages such as aiding in clinical decision support and facilitating medical education through their ability to process queries and analyze ophthalmic imaging and clinical cases. However, their utilization also raises ethical concerns regarding data privacy, potential misinformation, and biases inherent in the datasets used. Awareness of these concerns should be addressed in order to optimize its utility in the healthcare setting. More importantly, promoting responsible and careful use by consumers should be practiced.

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Exploring the Test-Taking Capabilities of Chatbots—From Surgeon to Sommelier

Cited by 5 publications

References 10 publications

The ability of artificial intelligence tools to formulate orthopaedic clinical decisions in comparison to human clinicians: An analysis of ChatGPT 3.5, ChatGPT 4, and Bard

The ability of artificial intelligence tools to formulate orthopaedic clinical decisions in comparison to human clinicians: An analysis of ChatGPT 3.5, ChatGPT 4, and Bard

Advances in Artificial Intelligence Chatbot Technology in Ophthalmology—Reply

Ethical considerations for large language models in ophthalmology

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