ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2016
Recognizing Question Entailment for Medical Question Answering.
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 10 papers.
What it found
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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
10 citing papers in PubMed.
- Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models.Findings of ACL. ACL · 2024Article
- Article
- MT-clinical BERT: scaling clinical information extraction with multitask learning.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Identification of Semantically Similar Sentences in Clinical Notes: Iterative Intermediate Training Using Multi-Task Learning.JMIR medical informatics · 2020Article
- Enhancing Question Answering by Injecting Ontological Knowledge through Regularization.Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing · 2020Article
- Consumer health information and question answering: helping consumers find answers to their health-related information needs.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- A question-entailment approach to question answering.BMC bioinformatics · 2019Article
- On the Role of Question Summarization and Information Source Restriction in Consumer Health Question Answering.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- Qcorp: an annotated classification corpus of Chinese health questions.BMC medical informatics and decision making · 2018Article
- Resource and Response Type Classification for Consumer Health Question Answering.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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the increasing heterogeneity and specialization of medical texts, automated question answering is becoming more and more challenging. In this context, answering a given medical question by retrieving similar questions that are already answered by human experts seems to be a promising solution. In this paper, we propose a new approach for the detection of similar questions based on Recognizing Question Entailment (RQE). In particular, we consider Frequently Asked Question (FAQs) as a valuable and widespread source of information. Our final goal is to automatically provide an existing answer if FAQ similar to a consumer health question exists. We evaluate our approach using consumer health questions received by the National Library of Medicine and FAQs collected from NIH websites. Our first results are promising and suggest the feasibility of our approach as a valuable complement to classic question answering approaches.
Indexed as
Identifiers
28269825PMC5333286What 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.