ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2023
Towards an Open-Source Platform to Harmonize and Share Research Results from COVID-19 Interventional and Observational Studies.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As the SARS-CoV-2 virus continues to remain a universal threat on a global scale, a large number of COVID-19 clinical trials and observational studies are being conducted and published. Currently, 9,202 COVID-19 clinical trials have been registered on ClinicalTrials.gov and 293,187 COVID-19 articles were indexed in PubMed. To fully capitalize on the voluminous number of publications reporting COVID-19 interventional and observational studies, their results should be freely accessible via an open-source harmonized shared resource. We introduced ReMeDy (https://remedy.mssm.edu/), an intelligent integrative informatics platform aimed to harmonize and cross-link diverse COVID-19 trial outcomes and observational data. We tested the potential of the platform by uploading 52 COVID-19 clinical trials and 48 COVID-19 observational retrospective studies. ReMeDy was validated based on its capability to store and organize diverse data. The next steps include developing a crowdsourcing functionality coupled with automated outcome extraction using natural language processing.
Identifiers
37350901PMC10283106What 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.