Clinical Value of Predicting Individual Treatment Effects for Intensive Blood Pressure Therapy: A Machine Learning Experiment to Estimate Treatment Effects from Randomized Trial Data [RETRACTED]
- DOI
- 10.1161/circoutcomes.118.005010
- Published
- 2019-03
- Container
- Circulation: Cardiovascular Quality and Outcomes
- Publisher
- Ovid Technologies (Wolters Kluwer Health)
- Open access
- unknown
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serious concern Score 29/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1161/circoutcomes.118.005010,
title = {Clinical Value of Predicting Individual Treatment Effects for Intensive Blood Pressure Therapy: A Machine Learning Experiment to Estimate Treatment Effects from Randomized Trial Data [RETRACTED]},
author = {Tony Duan and Pranav Rajpurkar and Dillon Laird and Andrew Y. Ng and Sanjay Basu},
year = {2019},
journal = {Circulation: Cardiovascular Quality and Outcomes},
doi = {10.1161/circoutcomes.118.005010},
url = {https://doi.org/10.1161/circoutcomes.118.005010}
}RIS
TY - JOUR TI - Clinical Value of Predicting Individual Treatment Effects for Intensive Blood Pressure Therapy: A Machine Learning Experiment to Estimate Treatment Effects from Randomized Trial Data [RETRACTED] AU - Tony Duan AU - Pranav Rajpurkar AU - Dillon Laird AU - Andrew Y. Ng AU - Sanjay Basu PY - 2019 JO - Circulation: Cardiovascular Quality and Outcomes DO - 10.1161/circoutcomes.118.005010 UR - https://doi.org/10.1161/circoutcomes.118.005010 ER -
APA
Duan, T., Rajpurkar, P., Laird, D., Ng, A. Y., & Basu, S. (2019). Clinical Value of Predicting Individual Treatment Effects for Intensive Blood Pressure Therapy: A Machine Learning Experiment to Estimate Treatment Effects from Randomized Trial Data [RETRACTED]. Circulation: Cardiovascular Quality and Outcomes. https://doi.org/10.1161/circoutcomes.118.005010
Source records
- crossref · retrieved 2026-09-25T08:07:26.737Z