Health AI Central
Peer-Reviewed Publication
Res Sq2026May 21, 2026Journal Article

Longitudinal Language-Model Reasoning Enables Automated Labeling of Lung Cancer Recurrence from Unstructured Clinical Records.

Carlotta S Hoelzle1,2, Johannes Brandt2, Jonathan C Mueller1, Maximiliano Klug1, Julian Westphal1, Daniel Rueckert2,3,4, Maulik Chevli2, Florian J Fintelmann1
1Department of Radiology, Massachusetts General Hospital, Boston, United States of America.
2Chair of AI in Healthcare and Medicine, Technical University of Munich, Munich, Germany.
3Department of Computing, Imperial College London, London, UK.
4Munich Center for Machine Learning (MCML), Munich, Germany.
PubMed PMC DOI PDF

Abstract

Many clinical endpoints are rarely captured as structured variables, necessitating labor-intensive manual abstraction from longitudinal narratives. We present SCRIBE, an open-source, training-free framework that extracts temporally precise, auditable clinical labels from unstructured records using only narrative text. SCRIBE utilizes multi-stage large language model reasoning to reconcile longitud…

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