Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Using supervised machine learning classifiers to estimate likelihood of participating in clinical trials of a de-identified version of ResearchMatch
20
Zitationen
6
Autoren
2020
Jahr
Abstract
The results show sufficient evidence that there are meaningful correlations amongst predictor variables and outcome variable in the datasets analysed using the supervised machine learning classifiers. These approaches show promise in identifying individuals who may be more likely to participate when offered an opportunity for a clinical trial.
Ähnliche Arbeiten
World Medical Association Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects
2003 · 10.819 Zit.
Estimating the mean and variance from the median, range, and the size of a sample
2005 · 8.956 Zit.
SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials
2013 · 6.963 Zit.
The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research
2020 · 5.261 Zit.
The global landscape of AI ethics guidelines
2019 · 4.566 Zit.