Forecasting cancer: from precision to predictive medicine

被引：9

作者：

Fertig, Elana J. ^{[1
,2
,3
,4
,5
]}

Jaffee, Elizabeth M. ^{[1
,2
,3
]}

Macklin, Paul ^{[6
]}

Stearns, Vered ^{[1
]}

Wang, Chenguang ^{[1
,7
]}

机构：

[1] Johns Hopkins Univ, Sch Med, Sidney Kimmel Comprehens Canc Ctr, Dept Oncol, Baltimore, MD 21218 USA

[2] Johns Hopkins Univ, Sch Med, Convergence Inst, Baltimore, MD 21218 USA

[3] Johns Hopkins Univ, Sch Med, Bloomberg Kimmel Immunol Inst, Baltimore, MD 21218 USA

[4] Johns Hopkins Univ, Whiting Sch Engn, Dept Appl Math & Stat, Baltimore, MD 21218 USA

[5] Johns Hopkins Univ, Sch Med, Dept Biomed Engn, Baltimore, MD 21218 USA

[6] Indiana Univ, Dept Intelligent Syst Engn, Bloomington, IN USA

[7] Johns Hopkins Univ Bloomberg, Sch Publ Hlth, Dept Biostat, Baltimore, MD USA

来源：

MED | 2021年 / 2卷 / 09期

关键词：

D O I：

10.1016/j.medj.2021.08.007

中图分类号：

R-3 [医学研究方法]; R3 [基础医学];

学科分类号：

1001 ;

摘要：

Tumor evolution drives tumor progression, therapeutic resistance, and metastasis. Therefore, new predictive medicine strategies that adapt with a tumor are needed to improve patient outcomes. The techniques used in weather prediction are mathematically proven to enable prediction of evolving systems, and thus provide a framework for a new predictive medicine paradigm for cancer.

引用

页码：1004 / 1010

页数：7

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