Cited By
View all- McDonnell K(2023)Leveraging the Academic Artificial Intelligence Silecosystem to Advance the Community Oncology EnterpriseJournal of Clinical Medicine10.3390/jcm1214483012:14(4830)Online publication date: 21-Jul-2023
Generative Adversarial Networks in Precision Oncology
Authors: 
Leandro von Werra, Marcel Schöngens, Ece D. Gamsiz Uzun, 
Carsten EickhoffAuthors Info & Claims
Leandro von Werra, Marcel Schöngens, Ece D. Gamsiz Uzun, Carsten EickhoffAuthors Info & ClaimsPages 145 - 148
Abstract
Precision medicine strives to deliver improved care based on genetic patient information. Towards this end, it is crucial to find effective data representations on which to perform matching and inference operations. We develop and evaluate a generative adversarial neural network (GAN) approach to representation learning with the goal of patient-centric literature retrieval and treatment recommendation in precision oncology. Several large-scale corpora including the COSMIC Cancer Gene Census, COSMIC Mutation Data, Genomic Data Commons (GDC) and 26M MEDLINE abstracts are used to train GANs for synthesizing genetic mutation patterns that likely correspond to patient properties such as their demographics or cancer type. The introduction of GANs into the literature retrieval and treatment recommendation process results in significant improvements in performance by increasing the recall of a range of methods at stable precision. Finally, we propose a method to discover novel gene-gene interaction hypotheses to guide future research.
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Index Terms
- Generative Adversarial Networks in Precision Oncology
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Information & Contributors
Information
Published In
September 2019
273 pages
ISBN:9781450368810
DOI:10.1145/3341981
- General Chairs:
- Yi Fang,
- Yi Zhang,
- Program Chairs:
- James Allan,
- Krisztian Balog,
- Ben Carterette,
- Jiafeng Guo
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Association for Computing Machinery
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Publication History
Published: 26 September 2019
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- Short-paper
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- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
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ICTIR '19
Sponsor:
ICTIR '19: The 2019 ACM SIGIR International Conference on the Theory of Information Retrieval
October 2 - 5, 2019
CA, Santa Clara, USA
Acceptance Rates
ICTIR '19 Paper Acceptance Rate 20 of 41 submissions, 49%;
Overall Acceptance Rate 235 of 527 submissions, 45%
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View all- McDonnell K(2023)Leveraging the Academic Artificial Intelligence Silecosystem to Advance the Community Oncology EnterpriseJournal of Clinical Medicine10.3390/jcm1214483012:14(4830)Online publication date: 21-Jul-2023
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