Optimal dose escalation methods using deep reinforcement learning in phase I oncology trials-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Optimal dose escalation methods using deep reinforcement learning in phase I oncology trials

Published:2023-01-30 Issue:5 Volume:33 Page:639-652
ISSN:1054-3406
Container-title:Journal of Biopharmaceutical Statistics
language:en
Short-container-title:Journal of Biopharmaceutical Statistics

Author:

Matsuura Kentaro¹^ORCID,Sakamaki Kentaro²,Honda Junya³,Sozu Takashi⁴

Affiliation:

1. Department of Management Science, Graduate School of Engineering, Tokyo University of Science, Tokyo, Japan

2. Center for Data Science, Yokohama City University Yokohama, Japan

3. Department of Systems Science, Graduate School of Informatics, Kyoto University Kyoto, Japan

4. Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science, Tokyo, Japan

Funder

JSPS KAKENHI

Publisher

Informa UK Limited

Subject

Pharmacology (medical),Pharmacology,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/10543406.2023.2170402

Reference20 articles.

1. Stan: A Probabilistic Programming Language

2. Semiparametric dose finding methods

3. Dose-Finding Designs for Early-Phase Cancer Clinical Trials

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP