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Evaluating AI chatbots in neurological function test interpretation for brain tumor surgery.

Jeeyoung Lee1, Eun Ji Lee2, Young Il Kim3

  • 1College of Medicine, Hallym University, Chuncheon, Korea.

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Summary

Large language models (LLMs) can accurately explain complex neuropsychological tests for brain tumor patients. These AI tools improve understanding and communication in neurosurgical care.

Keywords:
Artificial intelligenceBrain tumor patientsLarge language modelsNeuropsychological testsPatient communication

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Area of Science:

  • Neuroscience
  • Artificial Intelligence
  • Medical Communication

Background:

  • Neuropsychological tests are crucial for brain tumor patient evaluation and surgical planning.
  • The complexity of these tests can be a barrier for patient and junior clinician comprehension.
  • The utility of large language model (LLM)-based chatbots for interpreting neuropsychological tests is unexplored.

Purpose of the Study:

  • To assess the accuracy and patient-friendliness of LLM-generated explanations of neuropsychological tests.
  • To evaluate LLMs' potential to support communication in neurosurgical care for brain tumor patients.

Main Methods:

  • Twenty patients undergoing pre-surgical neuropsychological testing for brain tumors were included.
  • Three LLMs (ChatGPT, Copilot, Perplexity) were prompted with standardized questions about five specific tests.
  • Responses were evaluated for readability, understandability (using modified Patient Education Materials Assessment Tool), and expert-rated accuracy.

Main Results:

  • LLM responses showed readability scores between grades 9.6-11.0.
  • ChatGPT achieved the highest understandability (83.2%), excelling in explaining test purpose and methodology.
  • Perplexity demonstrated strong result interpretation and overall accuracy, with patients rating it highly for understandability and usefulness.

Conclusions:

  • LLMs can generate accurate and understandable explanations of neuropsychological tests.
  • These AI tools show promise in enhancing multidisciplinary care and patient communication within neurosurgery for brain tumors.