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Using supervised machine learning classifiers to estimate likelihood of participating in clinical trials of a de-identified version of ResearchMatch
INTRODUCTION: Lack of participation in clinical trials (CTs) is a major barrier for the evaluation of new pharmaceuticals and devices. Here we report the results of the analysis of a dataset from ResearchMatch, an online clinical registry, using supervised machine learning approaches and a deep lear...
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| Veröffentlicht in: | J Clin Transl Sci |
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| Hauptverfasser: | , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Cambridge University Press
2020
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8057403/ https://ncbi.nlm.nih.gov/pubmed/33948264 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1017/cts.2020.535 |
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