Article

Large Language Models Improve Cancer Survival Prediction Using Real-World Clinical Notes

2025-08-19

Abstract excerpt

In medical documentation, vast amounts of unstructured text are generated that are still underutilized in current prognostic models. We investigate the potential of self-hosted large language models (LLM) to extract clinically meaningful, patient-specific information from routine clinical notes for personalized risk stratification in cancer care. We collected real-world medical notes from 2,708 non-small cell lung...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: b13cf0d5-f219-5c04-b66d-69f6c256f6ec
DOI: 10.1101/2025.08.17.25333835

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Large Language Models Improve Cancer Survival Prediction Using Real-World Clinical NotesDOI 10.1101/2025.08.17.25333835Read

The Transformative Potential of Large Language Models in Mining Electronic Health Records DataSemantic proximity Read

Metastasis Extraction from NSCLC Clinical Notes: A Retrospective Comparative Evaluation of Large Language Model-Based ClassificationSemantic proximity Read

Disease Risk Prediction Using Structured EHR Data: Can Generalist Large Language Models Match Specialized Clinical Foundation Models? A Comparative Evaluation with Fine-TuningSemantic proximity Read

Automated ICD-O-3 Coding of Real-World Pathology Reports Using Self-Hosted Large Language ModelsSemantic proximity Read

Language-model-based patient embedding using electronic health records facilitates phenotyping, disease forecasting, and progression analysisSemantic proximity Read

Longitudinal information extraction from clinical notes in rare diseases: an efficient approach with small language modelsSemantic proximity Read

Scalable information extraction from free text electronic health records using large language modelsSemantic proximity Read

Predicting Rectal Cancer Patient Survival with Dutch Radiology Reports using Natural Language Processing (NLP): The Role of Pretrained Language ModelsSemantic proximity Read

Summarizing Clinical Notes using LLMs for ICU Bounceback and Length-of-Stay PredictionSemantic proximity Read

Large language models improve transferability of electronic health record-based predictions across countries and coding systemsSemantic proximity Read

Toward Digital Twins in the Intensive Care Unit: A Medication Management Case StudySemantic proximity Read

Generation of guideline-based clinical decision trees in oncology using large language modelsSemantic proximity Read