ArticleCEUR workshop proceedings2016
Clinical Information Extraction at the CLEF eHealth Evaluation lab 2016.
Article in CEUR workshop proceedings, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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
11 citing papers in PubMed.
- An end-to-end system for explainable clinical coding across languages and diverse medical data sources.BMC medical informatics and decision making · 2026Article
- Article
- Cross-lingual Natural Language Processing on Limited Annotated Case/Radiology Reports in English and Japanese: Insights from the Real-MedNLP Workshop.Methods of information in medicine · 2024Article
- Improving biomedical entity linking for complex entity mentions with LLM-based text simplification.Database : the journal of biological databases and curation · 2024Article
- Query sampler: generating query sets for analyzing search engines using keyword research tools.PeerJ. Computer science · 2023Article
- Neural Translation and Automated Recognition of ICD-10 Medical Entities From Natural Language: Model Development and Performance Assessment.JMIR medical informatics · 2022Article
- Development and Validation of an Artificial Intelligence System to Optimize Clinician Review of Patient Records.JAMA network open · 2021Article
- A comprehensive study of mobility functioning information in clinical notes: Entity hierarchy, corpus annotation, and sequence labeling.International journal of medical informatics · 2021Article
- A computational ecosystem to support eHealth Knowledge Discovery technologies in Spanish.Journal of biomedical informatics · 2020Article
- Tweet Classification Toward Twitter-Based Disease Surveillance: New Data, Methods, and Evaluations.Journal of medical Internet research · 2019Article
- Clinical Natural Language Processing in languages other than English: opportunities and challenges.Journal of biomedical semantics · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
This paper reports on Task 2 of the 2016 CLEF eHealth evaluation lab which extended the previous information extraction tasks of ShARe/CLEF eHealth evaluation labs. The task continued with named entity recognition and normalization in French narratives, as offered in CLEF eHealth 2015. Named entity recognition involved ten types of entities including
Indexed as
Identifiers
29308065PMC5756095What 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.