ArticleJournal of biomedical informatics2011
AskHERMES: An online question answering system for complex clinical questions.
Article in Journal of biomedical informatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 2 of them syntheses that pooled it.
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
51 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Question answering systems for health professionals at the point of care-a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2024Pooled it
- Text summarization in the biomedical domain: a systematic review of recent research.Journal of biomedical informatics · 2014Pooled it
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- Sentences, entities, and keyphrases extraction from consumer health forums using multi-task learning.Journal of biomedical semantics · 2025Article
- Optimizing biomedical information retrieval with a keyword frequency-driven prompt enhancement strategy.BMC bioinformatics · 2024Article
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- What Would it Take to get Biomedical QA Systems into Practice?Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing · 2021Article
- Using Character-Level and Entity-Level Representations to Enhance Bidirectional Encoder Representation From Transformers-Based Clinical Semantic Textual Similarity Model: ClinicalSTS Modeling Study.JMIR medical informatics · 2020Article
- Knowledge extraction for assisted curation of summaries of bacterial transcription factor properties.Database : the journal of biological databases and curation · 2020Article
- Adapting and evaluating a deep learning language model for clinical why-question answering.JAMIA open · 2020Article
- A Light-Weight Text Summarization System for Fast Access to Medical Evidence.Frontiers in digital health · 2020Article
- "Similar query was answered earlier": processing of patient authored text for retrieving relevant contents from health discussion forum.Health information science and systems · 2019Article
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- How user intelligence is improving PubMed.Nature biotechnology · 2018Article
- Qcorp: an annotated classification corpus of Chinese health questions.BMC medical informatics and decision making · 2018Article
- Semantic annotation of consumer health questions.BMC bioinformatics · 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
8 authors.
Funding
Abstract
objectiveClinical questions are often long and complex and take many forms. We have built a clinical question answering system named AskHERMES to perform robust semantic analysis on complex clinical questions and output question-focused extractive summaries as answers.
designThis paper describes the system architecture and a preliminary evaluation of AskHERMES, which implements innovative approaches in question analysis, summarization, and answer presentation. Five types of resources were indexed in this system: MEDLINE abstracts, PubMed Central full-text articles, eMedicine documents, clinical guidelines and Wikipedia articles. MEASUREMENT: We compared the AskHERMES system with Google (Google and Google Scholar) and UpToDate and asked physicians to score the three systems by ease of use, quality of answer, time spent, and overall performance.
resultsAskHERMES allows physicians to enter a question in a natural way with minimal query formulation and allows physicians to efficiently navigate among all the answer sentences to quickly meet their information needs. In contrast, physicians need to formulate queries to search for information in Google and UpToDate. The development of the AskHERMES system is still at an early stage, and the knowledge resource is limited compared with Google or UpToDate. Nevertheless, the evaluation results show that AskHERMES' performance is comparable to the other systems. In particular, when answering complex clinical questions, it demonstrates the potential to outperform both Google and UpToDate systems.
conclusionsAskHERMES, available at http://www.AskHERMES.org, has the potential to help physicians practice evidence-based medicine and improve the quality of patient care.
Indexed as
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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.