Identifying Vulnerability Signatures Through Machine Learning In An Umbrella Trial For Glioblastoma

Matthew Lee; Nanyun Tang; Manmeet Ahluwalia; Ekokobe Fonkem; Karen L. Fink; Harshil Dhruv; Michael E. Berens; Sen Peng

Identifying Vulnerability Signatures Through Machine Learning In An Umbrella Trial For Glioblastoma

Matthew Lee
, Nanyun Tang
, Manmeet Ahluwalia
, Ekokobe Fonkem
, Karen L. Fink
, Harshil Dhruv
, Michael E. Berens
, Sen Peng

Research output: Contribution to journal › Article › peer-review

Original language	American English
Journal	Neuro-oncology
Volume	22
State	Published - Nov 2020

Disciplines

Medicine and Health Sciences

Cite this

@article{9bc2329ebfc146c484806d4ab4d8ed1b,

title = "Identifying Vulnerability Signatures Through Machine Learning In An Umbrella Trial For Glioblastoma",

author = "Matthew Lee and Nanyun Tang and Manmeet Ahluwalia and Ekokobe Fonkem and Fink, \{Karen L.\} and Harshil Dhruv and Berens, \{Michael E.\} and Sen Peng",

note = "Abstract. Glioblastoma is characterized by intra- and inter-tumoral heterogeneity. An umbrella trial tests multiple treatment arms depending on corresponding bi",

year = "2020",

month = nov,

language = "American English",

volume = "22",

journal = "Neuro-oncology",

}

TY - JOUR

T1 - Identifying Vulnerability Signatures Through Machine Learning In An Umbrella Trial For Glioblastoma

AU - Lee, Matthew

AU - Tang, Nanyun

AU - Ahluwalia, Manmeet

AU - Fonkem, Ekokobe

AU - Fink, Karen L.

AU - Dhruv, Harshil

AU - Berens, Michael E.

AU - Peng, Sen

N1 - Abstract. Glioblastoma is characterized by intra- and inter-tumoral heterogeneity. An umbrella trial tests multiple treatment arms depending on corresponding bi

PY - 2020/11

Y1 - 2020/11

UR - https://academic.oup.com/neuro-oncology/article-abstract/22/Supplement_2/ii6/5960475

M3 - Article

VL - 22

JO - Neuro-oncology

JF - Neuro-oncology

ER -

Identifying Vulnerability Signatures Through Machine Learning In An Umbrella Trial For Glioblastoma

Disciplines

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Cite this