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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