AI-Powered Neurogenetics: Supporting Patient's Evaluation with Chatbot
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View abstract on PubMed
Summary
This summary is machine-generated.Large language models like ChatGPT and Gemini show potential for assisting in neurogenetic disorder evaluations. However, GPT models performed better than Gemini, though both had diagnostic accuracy gaps and hallucinations, requiring expert oversight.
Area Of Science
- Neurogenetics
- Artificial Intelligence in Medicine
- Clinical Decision Support
Background
- Artificial intelligence (AI) and large language models (LLMs) offer potential benefits for healthcare professionals.
- This study investigates the utility of ChatGPT and Google's Gemini in the initial assessment of patients with suspected neurogenetic disorders.
Purpose Of The Study
- To evaluate the performance of ChatGPT and Gemini in assisting clinicians with neurogenetic disorder assessments.
- To determine if these AI tools can serve as valuable adjuncts in identifying clinical features, suggesting differential diagnoses, and guiding genetic testing strategies.
Main Methods
- Ninety questions were posed to ChatGPT (Versions 4o, 4, and 3.5) and Gemini.
- Questions covered clinical diagnosis, genetic inheritance, recurrence risks, genetic testing, and patient management.
- The assessment focused on six rare neurogenetic disorders: Hereditary Spastic Paraplegia (types 4 and 7), Huntington Disease, Fragile X-associated Tremor/Ataxia Syndrome, Becker Muscular Dystrophy, and FacioScapuloHumeral Muscular Dystrophy.
Main Results
- GPT chatbots demonstrated superior performance compared to Gemini.
- All AI chatbots exhibited significant limitations in diagnostic accuracy.
- A concerning frequency of hallucinations was observed across all tested AI models.
Conclusions
- AI tools can potentially enhance clinician capabilities in evaluating neurogenetic disorders.
- Effective utilization of these AI tools necessitates close collaboration and supervision by neurologists and geneticists.
- Meticulous oversight is crucial to mitigate diagnostic inaccuracies and AI-generated hallucinations.
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