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"Vertigo, likely peripheral": the dizzying rise of ChatGPT. | LitMetric

"Vertigo, likely peripheral": the dizzying rise of ChatGPT.

Eur Arch Otorhinolaryngol

Department of Otolaryngology-Head and Neck Surgery, National University Hospital, 1E Kent Ridge Rd, Singapore, 119228, Singapore.

Published: October 2023

AI Article Synopsis

  • This article explores the effectiveness of the AI model ChatGPT in identifying vestibular causes of dizziness, particularly through the use of Natural Language Processing (NLP).
  • Eight hypothetical clinical scenarios were presented to ChatGPT, and its responses were assessed for various factors such as clarity and accuracy.
  • While ChatGPT provided coherent and mostly accurate differentials for dizziness causes, it struggles with nuances of clinical decision-making and identifying atypical cases, indicating room for improvement as AI continues to evolve in the medical field.

Article Abstract

Purpose: The use of artificial intelligence (AI) in medical decision-making has once again come to the forefront with the prevalence of Natural Language Processing (NLP). In this exploratory article, we tested one such model, ChatGPT, for its ability to identify vestibular causes of dizziness METHODS: Eight hypothetical scenarios were presented to ChatGPT, which included varying clinical pictures and types of prompts. The responses given by ChatGPT were evaluated for coherence, clarity, consistency, accuracy, appropriateness, and recognition of limitations. ChatGPT provided coherent and logical responses.

Results: The model accurately provided differentials for both vestibular and non-vestibular causes of dizziness, with the correct diagnosis presented first in six of the cases, with important limitations CONCLUSION: Being an AI tool, ChatGPT lacks the ability to process certain nuances in clinical decision making, in both identifying atypical dizziness, as well as in recommending further examination steps to elucidate a clearer diagnosis. We believe that AI will continue to forge ahead in the medical field. Merging the immense knowledge base of AI programming with the nuances of clinical assessment and knowledge integration will surely enhance patient care in the years to come.

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Source
http://dx.doi.org/10.1007/s00405-023-08135-1DOI Listing

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