ReviewJournal of biomedical informatics2021
Searching for scientific evidence in a pandemic: An overview of TREC-COVID.
Review in Journal of biomedical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Enhancing Patient-Trial Matching With Large Language Models: A Scoping Review of Emerging Applications and Approaches.JCO clinical cancer informatics · 2025Article
- Large Language Models in Healthcare: A Bibliometric Analysis and Examination of Research Trends.Journal of multidisciplinary healthcare · 2025Article
- Searching COVID-19 Clinical Research Using Graph Queries: Algorithm Development and Validation.Journal of medical Internet research · 2024Article
- Novel informatics approaches to COVID-19 Research: From methods to applications.Journal of biomedical informatics · 2022Article
- Information retrieval and question answering: A case study on COVID-19 scientific literature.Knowledge-based systems · 2022Article
- Data science approaches to confronting the COVID-19 pandemic: a narrative review.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022Review
- Applications of natural language processing in ophthalmology: present and future.Frontiers in medicine · 2022Review
- A term-based and citation network-based search system for COVID-19.JAMIA open · 2021Article
- Information Retrieval in an Infodemic: The Case of COVID-19 Publications.Journal of medical Internet research · 2021Article
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
We present an overview of the TREC-COVID Challenge, an information retrieval (IR) shared task to evaluate search on scientific literature related to COVID-19. The goals of TREC-COVID include the construction of a pandemic search test collection and the evaluation of IR methods for COVID-19. The challenge was conducted over five rounds from April to July 2020, with participation from 92 unique teams and 556 individual submissions. A total of 50 topics (sets of related queries) were used in the evaluation, starting at 30 topics for Round 1 and adding 5 new topics per round to target emerging topics at that state of the still-emerging pandemic. This paper provides a comprehensive overview of the structure and results of TREC-COVID. Specifically, the paper provides details on the background, task structure, topic structure, corpus, participation, pooling, assessment, judgments, results, top-performing systems, lessons learned, and benchmark datasets.
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.