# How essential are unstructured clinical narratives and information fusion to clinical trial recruitment?

arXiv: https://arxiv.org/abs/1502.04049 · HTML: https://mlsanity.com/paper/1502.04049/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Feb 2015.

## Built on by (most cited first, 6 of 6)

- [CamemBERT-bio: Leveraging Continual Pre-training for Cost-Effective Models on French Biomedical Data](https://mlsanity.com/paper/2306.15550/) (2023)
- [Entity Decomposition with Filtering: A Zero-Shot Clinical Named Entity Recognition Framework](https://mlsanity.com/paper/2407.04629/) (2024)
- [Onco-Retriever: Generative Classifier for Retrieval of EHR Records in Oncology](https://mlsanity.com/paper/2404.06680/) (2024)
- [Learning structures of the French clinical language:development and validation of word embedding models using 21 million clinical reports from electronic health records](https://mlsanity.com/paper/2207.12940/) (2022)
- [MORE-CLEAR: Multimodal Offline Reinforcement learning for Clinical notes Leveraged Enhanced State Representation](https://mlsanity.com/paper/2508.07681/) (2025)
- [MedOrchestra: A Hybrid Cloud-Local LLM Approach for Clinical Data Interpretation](https://mlsanity.com/paper/2505.23806/) (2025)

## Abstract (arXiv)

Electronic health records capture patient information using structured controlled vocabularies and unstructured narrative text. While structured data typically encodes lab values, encounters and medication lists, unstructured data captures the physician's interpretation of the patient's condition, prognosis, and response to therapeutic intervention. In this paper, we demonstrate that information extraction from unstructured clinical narratives is essential to most clinical applications. We perform an empirical study to validate the argument and show that structured data alone is insufficient in resolving eligibility criteria for recruiting patients onto clinical trials for chronic lymphocytic leukemia (CLL) and prostate cancer. Unstructured data is essential to solving 59% of the CLL trial criteria and 77% of the prostate cancer trial criteria. More specifically, for resolving eligibility criteria with temporal constraints, we show the need for temporal reasoning and information integration with medical events within and across unstructured clinical narratives and structured data.