Inductive reasoning with large language models: a simulated randomized controlled trial for epilepsy.

ABSTRACT:

Importance

The analysis of electronic medical records at scale to learn from clinical experience is currently very challenging. The integration of artificial intelligence (AI), specifically foundational large language models (LLMs), into an analysis pipeline may overcome some of the current limitations of modest input sizes, inaccuracies, biases, and incomplete knowledge bases.

Objective

To explore the effectiveness of using an LLM for generating realistic clinical data and other LLMs for summarizing and synthesizing information in a model system, simulating a randomized clinical trial (RCT) in epilepsy to demonstrate the potential of inductive reasoning via medical chart review.

Design

An LLM-generated simulated RCT based on a RCT for treatment with an antiseizure me

SUBMITTER: Goldenholz DM 

PROVIDER: S-EPMC10984041 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature