Evaluating Generative AI's Ability to Identify Cancer Subtypes in Publicly Available Structured Genetic Datasets.

ABSTRACT:

Background

Genetic data play a crucial role in diagnosing and treating various diseases, reflecting a growing imperative to integrate these data into clinical care. However, significant barriers such as the structure of electronic health records (EHRs), insurance costs for genetic testing, and the interpretability of genetic results impede this integration.

Methods

This paper explores solutions to these challenges by combining recent technological advances with informatics and data science, focusing on the diagnostic potential of artificial intelligence (AI) in cancer research. AI has historically been applied in medical research with limited success, but recent developments have led to the emergence of large language models (LLMs). These transformer-based generative AI mode

SUBMITTER: Hillis E 

PROVIDER: S-EPMC11508243 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature