AI/ML-Derived Whole-Genome Predictor Prospectively and Clinically Predicts Survival and Response to Treatment in Brain Cancer

Sri Priya Ponnapalli; Penelope Miron; Kristy L.S. Miskimen; Kristin A. Waite; Nadiya Sosonkina; Sara E. Coppens; Anthony C. Bryan; Estevan P. Kiernan; Huanming Yang; Jay Bowen; Ghunwa A. Nakouzi; Jill S. Barnholtz-Sloan; Andrew E. Sloan; Tiffany R. Hodges; Orly Alter

doi:10.1145/3624062.3624078

AI/ML-Derived Whole-Genome Predictor Prospectively and Clinically Predicts Survival and Response to Treatment in Brain Cancer

Sri Priya Ponnapalli
, Penelope Miron
, Kristy L.S. Miskimen
, Kristin A. Waite
, Nadiya Sosonkina
, Sara E. Coppens
, Anthony C. Bryan
, Estevan P. Kiernan
, Huanming Yang
, Jay Bowen
, Ghunwa A. Nakouzi
, Jill S. Barnholtz-Sloan
, Andrew E. Sloan
, Tiffany R. Hodges
, Orly Alter

University of Utah
Case Western Reserve University
National Institutes of Health
HudsonAlpha Institute for Biotechnology
Nationwide Children’s Hospital
Illumina, Inc.
BGI-Shenzhen
Piedmont Healthcare

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Original language	English
Title of host publication	Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023
Publisher	Association for Computing Machinery
Pages	117-118
Number of pages	2
ISBN (Electronic)	9798400707858
DOIs	https://doi.org/10.1145/3624062.3624078
State	Published - 12 Nov 2023
Externally published	Yes
Event	2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 - Denver, United States Duration: 12 Nov 2023 → 17 Nov 2023

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023
Country/Territory	United States
City	Denver
Period	12/11/23 → 17/11/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Accurate
Data-Agnostic Algorithms
Eigengene
Fair and Responsible Artificial Intelligence and Machine Learning (AI/ML)
Generalizable
Interpretable
Multi-Tensor Comparative Spectral Decompositions
Platform- and Reference Genome-Agnostic Whole-Genome Predictors
Precise
Prospective and Clinical Prediction of a Glioblastoma (GBM) Patient's Outcome
Quantum Mechanics
Retrospective Clinical Trial
Singular Value Decomposition (SVD)
and Actionable Models

Access to Document

10.1145/3624062.3624078

Cite this

Ponnapalli, S. P., Miron, P., Miskimen, K. L. S., Waite, K. A., Sosonkina, N., Coppens, S. E., Bryan, A. C., Kiernan, E. P., Yang, H., Bowen, J., Nakouzi, G. A., Barnholtz-Sloan, J. S., Sloan, A. E., Hodges, T. R., & Alter, O. (2023). AI/ML-Derived Whole-Genome Predictor Prospectively and Clinically Predicts Survival and Response to Treatment in Brain Cancer. In Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 (pp. 117-118). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3624062.3624078

Ponnapalli, Sri Priya ; Miron, Penelope ; Miskimen, Kristy L.S. et al. / AI/ML-Derived Whole-Genome Predictor Prospectively and Clinically Predicts Survival and Response to Treatment in Brain Cancer. Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023. Association for Computing Machinery, 2023. pp. 117-118 (ACM International Conference Proceeding Series).

@inproceedings{3e120b4ed7cc4b3f976a76931f8a025f,

title = "AI/ML-Derived Whole-Genome Predictor Prospectively and Clinically Predicts Survival and Response to Treatment in Brain Cancer",

keywords = "Accurate, Data-Agnostic Algorithms, Eigengene, Fair and Responsible Artificial Intelligence and Machine Learning (AI/ML), Generalizable, Interpretable, Multi-Tensor Comparative Spectral Decompositions, Platform- and Reference Genome-Agnostic Whole-Genome Predictors, Precise, Prospective and Clinical Prediction of a Glioblastoma (GBM) Patient's Outcome, Quantum Mechanics, Retrospective Clinical Trial, Singular Value Decomposition (SVD), and Actionable Models",

author = "Ponnapalli, \{Sri Priya\} and Penelope Miron and Miskimen, \{Kristy L.S.\} and Waite, \{Kristin A.\} and Nadiya Sosonkina and Coppens, \{Sara E.\} and Bryan, \{Anthony C.\} and Kiernan, \{Estevan P.\} and Huanming Yang and Jay Bowen and Nakouzi, \{Ghunwa A.\} and Barnholtz-Sloan, \{Jill S.\} and Sloan, \{Andrew E.\} and Hodges, \{Tiffany R.\} and Orly Alter",

year = "2023",

month = nov,

day = "12",

doi = "10.1145/3624062.3624078",

language = "英语",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

pages = "117--118",

booktitle = "Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023",

note = "2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023 ; Conference date: 12-11-2023 Through 17-11-2023",

}

Ponnapalli, SP, Miron, P, Miskimen, KLS, Waite, KA, Sosonkina, N, Coppens, SE, Bryan, AC, Kiernan, EP, Yang, H, Bowen, J, Nakouzi, GA, Barnholtz-Sloan, JS, Sloan, AE, Hodges, TR & Alter, O 2023, AI/ML-Derived Whole-Genome Predictor Prospectively and Clinically Predicts Survival and Response to Treatment in Brain Cancer. in Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 117-118, 2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023, Denver, United States, 12/11/23. https://doi.org/10.1145/3624062.3624078

AI/ML-Derived Whole-Genome Predictor Prospectively and Clinically Predicts Survival and Response to Treatment in Brain Cancer. / Ponnapalli, Sri Priya; Miron, Penelope; Miskimen, Kristy L.S. et al.
Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023. Association for Computing Machinery, 2023. p. 117-118 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - AI/ML-Derived Whole-Genome Predictor Prospectively and Clinically Predicts Survival and Response to Treatment in Brain Cancer

AU - Ponnapalli, Sri Priya

AU - Miron, Penelope

AU - Miskimen, Kristy L.S.

AU - Waite, Kristin A.

AU - Sosonkina, Nadiya

AU - Coppens, Sara E.

AU - Bryan, Anthony C.

AU - Kiernan, Estevan P.

AU - Yang, Huanming

AU - Bowen, Jay

AU - Nakouzi, Ghunwa A.

AU - Barnholtz-Sloan, Jill S.

AU - Sloan, Andrew E.

AU - Hodges, Tiffany R.

AU - Alter, Orly

PY - 2023/11/12

Y1 - 2023/11/12

KW - Accurate

KW - Data-Agnostic Algorithms

KW - Eigengene

KW - Fair and Responsible Artificial Intelligence and Machine Learning (AI/ML)

KW - Generalizable

KW - Interpretable

KW - Multi-Tensor Comparative Spectral Decompositions

KW - Platform- and Reference Genome-Agnostic Whole-Genome Predictors

KW - Precise

KW - Prospective and Clinical Prediction of a Glioblastoma (GBM) Patient's Outcome

KW - Quantum Mechanics

KW - Retrospective Clinical Trial

KW - Singular Value Decomposition (SVD)

KW - and Actionable Models

UR - https://www.scopus.com/pages/publications/85178152736

U2 - 10.1145/3624062.3624078

DO - 10.1145/3624062.3624078

M3 - 会议稿件

AN - SCOPUS:85178152736

T3 - ACM International Conference Proceeding Series

SP - 117

EP - 118

BT - Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023

PB - Association for Computing Machinery

T2 - 2023 International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023

Y2 - 12 November 2023 through 17 November 2023

ER -

Ponnapalli SP, Miron P, Miskimen KLS, Waite KA, Sosonkina N, Coppens SE et al. AI/ML-Derived Whole-Genome Predictor Prospectively and Clinically Predicts Survival and Response to Treatment in Brain Cancer. In Proceedings of 2023 SC Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, SC Workshops 2023. Association for Computing Machinery. 2023. p. 117-118. (ACM International Conference Proceeding Series). doi: 10.1145/3624062.3624078

AI/ML-Derived Whole-Genome Predictor Prospectively and Clinically Predicts Survival and Response to Treatment in Brain Cancer

Publication series

Conference

UN SDGs

Keywords

Access to Document

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