Atul Jain

Strategies for Deploying Large Language Models for Ascertaining Clinical Outcomes and Sites of Metastases From Radiology Impressions in Patients With Cancer.

Open-source LLMs, when fine-tuned using labeled data, can effectively automate the ascertainment of key radiophenotypic variables using only the impression section of radiology reports, without the full report text, suggesting that these models may provide a scalable approach for phenotypic characterization of patients with cancer in real-world clinical settings.