firdaus, firdaus (2019) Breast Cancer Classification Using Deep Learning. Proceedings of 2018 International Conference on Electrical Engineering and Computer Science, ICECOS 2018 (860518). pp. 237-242.
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Abstract
Breast cancer has been identified as the most widespread cancer amongst women and also the major cause of female cancer death all over the world. In this paper, we build the classification model of a person who is exposed to breast cancer based on recurrences-event and no-recurrences event. This classification using datasets from the University of Medicine Center, Institute Of Oncology, Ljublijana, Yugoslavia of the 286 datasets consist 2 classes, 201 No-Recurrences-Events classes, 85 Recurrences-events classes and 10 attributes including classes. The algorithm used for breast cancer classification is the Multilayer Perceptron algorithm with the accuracy level of 96.5% and high evaluation is 69.93% in 8-fold cross validation from 10-fold cross validation. © 2018 IEEE.
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. |
| Divisions: | 09-Faculty of Computer Science > 56201-Computer Systems (S1) |
| Depositing User: | Mr Firdaus Firdaus |
| Date Deposited: | 17 Mar 2023 14:55 |
| Last Modified: | 17 Mar 2023 14:55 |
| URI: | http://repository.unsri.ac.id/id/eprint/90720 |
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