Using machine learning to model dose-response relationships-Reference-Cited by-同舟云学术

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Using machine learning to model dose-response relationships

Published:2016-05-30 Issue:6 Volume:22 Page:860-867
ISSN:1356-1294
Container-title:Journal of Evaluation in Clinical Practice
language:en
Short-container-title:J Eval Clin Pract

Author:

Linden Ariel¹²,Yarnold Paul R³⁴,Nallamothu Brahmajee K⁵

Affiliation:

1. Linden Consulting Group, LLC; Ann Arbor MI USA

2. Division of General Medicine; Medical School-University of Michigan; Ann Arbor MI USA

3. Optimal Data Analysis, LLC; Chicago IL USA

4. Southern Network on Adverse Reactions (SONAR), College of Pharmacy; University of South Carolina; Columbia SC USA

5. Division of Cardiovascular Diseases, Department of Internal Medicine; Medical School-University of Michigan; Ann Arbor MI USA

Funder

National Cancer Institute

Publisher

Wiley

Subject

Public Health, Environmental and Occupational Health,Health Policy

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/jep.12573/fullpdf

Reference37 articles.

1. Opportunities for integration of pharmacokinetics, pharmacodynamics, and toxicokinetics in rational drug development;Peck;Journal of Pharmaceutical Sciences,1992

2. A smooth covariate rank transformation for use in regression models with a sigmoid dose-response function;Royston;Stata Journal,2014

3. An automated fitting procedure and software for dose-response curves with multiphasic features;Di Veroli;Scientific reports,2015

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