BIO

My name is Yash Alva, I am currently a junior Public Health major student at Florida State University and I am a part of the UROP Program.

Informatics Supporting Patients’ Understanding of Lab Results: Identifying Patients’ Questions about Lab Results

Abstract

The LabGenie project aims to address the challenge of patients, especially the elderly, in understanding medical lab test results and acting upon them. Even though generative AI models such as ChatGPT can answer questions, patients may not know what questions to ask, and they may also generate answers with inaccurate information or hallucinations. In the eHealth Lab, we are developing informatics strategies to augment large language models (LLM) by 1) identifying credible health sources for lab test result interpretation, and 2) curating these sources to computable format. As such, they can be used for question prompt enrichment with human input and retrieval-augmented generation (RAG). The ultimate goal is to integrate the RAG-based LLMs with a user-friendly interface for patients. LabGenie seeks to allow patients with low health literacy to ask contextualized questions and make informed health decisions with their providers confidently. The research involves literature reviews on LLM capabilities in clinical settings, converting lab result interpretation into a table format, and evaluating strengths and weaknesses of different LLMs in answering lab result questions. These procedures aim to provide meaningful results to train LLMs and contribute to the creation of LabGenie.

Keywords: Ai, LLMS, lab reports, lab data