Article

Performance of Google NotebookLM for AI-assisted data extraction and consensus statement generation in a heterogenous systematic review on inflammatory bowel disease, obesity, and cardiometabolic comorbidities: A Methodological Report

2026-06-26

Abstract excerpt

<h4>Background</h4> Large language models (LLMs) offer promise for systematic review data extraction, but performance in complex multidisciplinary domains and utility for clinical statement generation remain insufficiently described. <h4>Objectives</h4> To evaluate Google NotebookLM for AI-assisted data extraction and RAND/UCLA consensus statement generation in a systematic review of IBD, obesity, and cardiometa...

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Literature Corpus work: 65313c16-3f49-5651-847c-d3689cde58f3
DOI: 10.64898/2026.06.16.26355773

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