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
收藏
页码:1004 / 1010
页数:7
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