ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2016
Ensembles of NLP Tools for Data Element Extraction from Clinical Notes.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Generative AI models: the next anaesthetic agent?British journal of anaesthesia · 2025Article
- Predicting positiveHeliyon · 2025Article
- Article
- A model of integrating convolution and BiGRU dual-channel mechanism for Chinese medical text classifications.PloS one · 2023Article
- Predicting COVID-19 county-level case number trend by combining demographic characteristics and social distancing policies.JAMIA open · 2022Article
- Article
- The Construction Model of the TCM Clinical Knowledge Coding Database Based on Knowledge Organization.BioMed research international · 2022Article
- Different Data Mining Approaches Based Medical Text Data.Journal of healthcare engineering · 2021Review
- medExtractR: A targeted, customizable approach to medication extraction from electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Privacy-preserving model learning on a blockchain network-of-networks.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- A natural language processing algorithm to extract characteristics of subdural hematoma from head CT reports.Emergency radiology · 2019Article
- Assessing Information Congruence of Documented Cardiovascular Disease between Electronic Dental and Medical Records.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Natural Language Processing (NLP) is essential for concept extraction from narrative text in electronic health records (EHR). To extract numerous and diverse concepts, such as data elements (i.e., important concepts related to a certain medical condition), a plausible solution is to combine various NLP tools into an ensemble to improve extraction performance. However, it is unclear to what extent ensembles of popular NLP tools improve the extraction of numerous and diverse concepts. Therefore, we built an NLP ensemble pipeline to synergize the strength of popular NLP tools using seven ensemble methods, and to quantify the improvement in performance achieved by ensembles in the extraction of data elements for three very different cohorts. Evaluation results show that the pipeline can improve the performance of NLP tools, but there is high variability depending on the cohort.
Indexed as
Identifiers
28269947PMC5333200What 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.