Ability of Large Language Models to Extract PD-L1 Biomarker Details From Electronic Health Records

NEW ROCHELLE, N.Y., March 5, 2025 /PRNewswire/ — A new study, published in the peer-reviewed journal AI in Precision Oncology, examines the ability of large language models (LLMs) to rapidly extract PD-L1 biomarker details from the electronic health record (EHR). Click here to read the article now.

PD-L1 biomarker testing guides cancer treatment decisions. These results are difficult to access because laboratory reports are unstructured and require clinical expertise to interpret.

Aaron Cohen, MD, from Flatiron Health and NYU Langone School of Medicine, and coauthors, applied open-source LLMs to extract seven biomarker details relating to PD-L1 testing from the Flatiron Health US nationwide, EHR-derived database.

“LLMs, fine-tuned with high-quality labeled data, accurately extracted complex PD-L1 test details from EHRs despite considerable variability in cancer type, documentation and time,” reported the investigators.

“This study is a prime example of AI’s power to find needles in haystacks within massive medical records. By extracting critical biomarker data like PD-L1, AI is helping us provide better care, save valuable time, and improve patient outcomes. I commend these authors for their important work and outstanding manuscript. This is exactly the kind of research we aim to publish in AI in Precision Oncology,” says Douglas Flora, MD, Editor-in-Chief of AI in Precision Oncology.

About the Journal
AI in Precision Oncology is the only peer-reviewed journal dedicated to the advancement of artificial intelligence applications in clinical and precision oncology. Spearheaded by Editor-in-Chief Douglas Flora, MD and supported by a diverse and accomplished team of international experts, the Journal provides a high-profile forum for cutting-edge research and front matter highlighting important research and industry-related advances rapidly developing within the field. For complete information, visit the AI in Precision Oncology website.

About the Publisher
Mary Ann Liebert, Inc., a Sage company is a global media company dedicated to publishing and delivering impactful peer-reviewed research in biotechnology and life sciences, specialized clinical medicine, and public health and policy, and technology & engineering. Since its founding in 1980, the company has focused on providing critical insights and content that empower researchers and clinicians worldwide to drive innovation and discovery. 

Mary Ann Liebert, Inc. / Genetic Engineering News 
Media Contact: Kathryn Ryan
914-740-2250
kryan@liebertpub.com

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SOURCE Mary Ann Liebert, Inc.