Neurological history both twinned and queried by generative artificial intelligence.

ABSTRACT:

Background and objectives

We propose the use of GPT-4 to facilitate initial history-taking in neurology and other medical specialties. A large language model (LLM) could be utilized as a digital twin which could enhance queryable electronic medical record (EMR) systems and provide healthcare conversational agents (HCAs) to replace waiting-room questionnaires.

Methods

In this observational pilot study, we presented verbatim history of present illness (HPI) narratives from published case reports of headache, stroke, and neurodegenerative diseases. Three standard GPT-4 models were designated Models P: patient digital twin; N: neurologist to query Model P; and S: supervisor to synthesize the N-P dialogue into a derived HPI and formulate the differential diag

SUBMITTER: Lee JH 

PROVIDER: S-EPMC11782252 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature