ArticleJournal of the American Medical Informatics Association : JAMIA2019
Clinical trial cohort selection based on multi-level rule-based natural language processing system.
Article in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review on natural language processing systems for eligibility prescreening in clinical research.Journal of the American Medical Informatics Association : JAMIA · 2021Pooled it
- Benchmarking GPT-5, LLaMA, and Mistral for Clinical Named Entity Recognition in Ophthalmology Progress Notes.Translational vision science & technology · 2026Article
- Artificial intelligence in clinical trial participant recruitment and retention: A scoping review and meta-analysis.Journal of clinical and translational science · 2026Review
- Natural Language Processing in Support of Evidence-based Medicine: A Scoping Review.Findings of ACL. ACL · 2025Article
- Artificial intelligence for optimizing recruitment and retention in clinical trials: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Matching Patients to Clinical Trials using LLaMA 2 Embeddings and Siamese Neural Network.medRxiv : the preprint server for health sciences · 2024Article
- Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review.JMIR medical informatics · 2023Review
- LeafAI: query generator for clinical cohort discovery rivaling a human programmer.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- A case study in applying artificial intelligence-based named entity recognition to develop an automated ophthalmic disease registry.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2023Article
- Named Entity Recognition and Normalization for Alzheimer's Disease Eligibility Criteria.Proceedings. IEEE International Conference on Healthcare Informatics · 2023Article
- Artificial Intelligence Applied to clinical trials: opportunities and challenges.Health and technology · 2023Review
- How can natural language processing help model informed drug development?: a review.JAMIA open · 2022Review
- Identifying Patients With Hypoglycemia Using Natural Language Processing: Systematic Literature Review.JMIR diabetes · 2022Review
- Cohort Identification from Free-Text Clinical Notes Using SNOMED CT's Hierarchical Semantic Relations.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2022Article
- Applications of natural language processing in ophthalmology: present and future.Frontiers in medicine · 2022Review
- Clinical concept normalization with a hybrid natural language processing system combining multilevel matching and machine learning ranking.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- A transformation-based method for auditing the IS-A hierarchy of biomedical terminologies in the Unified Medical Language System.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Artificial intelligence approaches using natural language processing to advance EHR-based clinical research.The Journal of allergy and clinical immunology · 2020Review
- Cohort selection for clinical trials: n2c2 2018 shared task track 1.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Cohort Selection for Clinical Trials From Longitudinal Patient Records: Text Mining Approach.JMIR medical informatics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
objectiveIdentifying patients who meet selection criteria for clinical trials is typically challenging and time-consuming. In this article, we describe our clinical natural language processing (NLP) system to automatically assess patients' eligibility based on their longitudinal medical records. This work was part of the 2018 National NLP Clinical Challenges (n2c2) Shared-Task and Workshop on Cohort Selection for Clinical Trials. MATERIALS AND
methodsThe authors developed an integrated rule-based clinical NLP system which employs a generic rule-based framework plugged in with lexical-, syntactic- and meta-level, task-specific knowledge inputs. In addition, the authors also implemented and evaluated a general clinical NLP (cNLP) system which is built with the Unified Medical Language System and Unstructured Information Management Architecture. RESULTS AND DISCUSSION: The systems were evaluated as part of the 2018 n2c2-1 challenge, and authors' rule-based system obtained an F-measure of 0.9028, ranking fourth at the challenge and had less than 1% difference from the best system. While the general cNLP system didn't achieve performance as good as the rule-based system, it did establish its own advantages and potential in extracting clinical concepts.
conclusionOur results indicate that a well-designed rule-based clinical NLP system is capable of achieving good performance on cohort selection even with a small training data set. In addition, the investigation of a Unified Medical Language System-based general cNLP system suggests that a hybrid system combining these 2 approaches is promising to surpass the state-of-the-art performance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.