Cargando…
Cohort Selection for Clinical Trials From Longitudinal Patient Records: Text Mining Approach
BACKGROUND: Clinical trials are an important step in introducing new interventions into clinical practice by generating data on their safety and efficacy. Clinical trials need to ensure that participants are similar so that the findings can be attributed to the interventions studied and not to some...
Autores principales: | Spasic, Irena, Krzeminski, Dominik, Corcoran, Padraig, Balinsky, Alexander |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6913747/ https://www.ncbi.nlm.nih.gov/pubmed/31674914 http://dx.doi.org/10.2196/15980 |
Ejemplares similares
-
Text Mining of Adverse Events in Clinical Trials: Deep Learning Approach
por: Chopard, Daphne, et al.
Publicado: (2021) -
KLOSURE: Closing in on open–ended patient questionnaires with text mining
por: Spasić, Irena, et al.
Publicado: (2019) -
Sentiment Analysis in Health and Well-Being: Systematic Review
por: Zunic, Anastazia, et al.
Publicado: (2020) -
Facilitating the development of controlled vocabularies for metabolomics technologies with text mining
por: Spasić, Irena, et al.
Publicado: (2008) -
Clinical Text Data in Machine Learning: Systematic Review
por: Spasic, Irena, et al.
Publicado: (2020)