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On the Use of Neural Networks with Censored Time-to-Event Data
- Source :
- International Symposium on Mathematical and Computational Oncology-ISMCO 2020, International Symposium on Mathematical and Computational Oncology-ISMCO 2020, Oct 2020, Paris, France. pp.56-67, ⟨10.1007/978-3-030-64511-3_6⟩, Mathematical and Computational Oncology ISBN: 9783030645106, ISMCO
- Publication Year :
- 2020
- Publisher :
- HAL CCSD, 2020.
-
Abstract
- Motivation: The objective of this work is to confront artificial neural network models with time-to-event data, using specific ways to handle censored observations such as pseudo-observations and tailored loss functions.
- Subjects :
- 0303 health sciences
Artificial neural network
Computer science
business.industry
[SDV]Life Sciences [q-bio]
Machine learning
computer.software_genre
01 natural sciences
010104 statistics & probability
03 medical and health sciences
Survival data
Work (electrical)
Event data
Artificial intelligence
0101 mathematics
[MATH]Mathematics [math]
business
computer
ComputingMilieux_MISCELLANEOUS
030304 developmental biology
Subjects
Details
- Language :
- English
- ISBN :
- 978-3-030-64510-6
- ISBNs :
- 9783030645106
- Database :
- OpenAIRE
- Journal :
- International Symposium on Mathematical and Computational Oncology-ISMCO 2020, International Symposium on Mathematical and Computational Oncology-ISMCO 2020, Oct 2020, Paris, France. pp.56-67, ⟨10.1007/978-3-030-64511-3_6⟩, Mathematical and Computational Oncology ISBN: 9783030645106, ISMCO
- Accession number :
- edsair.doi.dedup.....b8b07c2bd531021ffb6e2584725e26ce
- Full Text :
- https://doi.org/10.1007/978-3-030-64511-3_6⟩