Abstract
This is models with the ability to detect and classify cancer is important in the industrial of healthcare. The most difficult aspect for such model is the classification of cancer, which can be addressed using machine learning methods. The methods are used to improve classification accuracy between system output and test data. The classification process becomes more difficult due to vast data information. This paper presents an overview on current development of cancer classification techniques using machine learning methods, which have received increasing attention within the area of healthcare. This review will mainly focus on the development of machine learning methods for classification of cancer diseases. Recently, there are various researchers proposed different kinds of methods for cancer classification. The results show that the successful of cancer classification is dependent on the machine learning models. Besides, various types of healthcare data used in the experiments would also be discussed in this paper. The development of many optimization methods for cancer classification has brought a lot of improvement in the healthcare field. There is demand for further improvements in optimization methods to develop better machine learning models for cancer classification.
| Original language | English |
|---|---|
| Title of host publication | 2021 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2021 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 392-395 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781665403436 |
| DOIs | |
| Publication status | Published - Jun 26 2021 |
| Event | 2021 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2021 - Virtual, Shah Alam, Malaysia Duration: Jun 26 2021 → … |
Publication series
| Name | 2021 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2021 - Proceedings |
|---|
Conference
| Conference | 2021 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2021 |
|---|---|
| Country/Territory | Malaysia |
| City | Virtual, Shah Alam |
| Period | 6/26/21 → … |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Artificial intelligence
- Cancer classification
- Machine learning
- Supervised
- Unsupervised
ASJC Scopus subject areas
- Artificial Intelligence
- Control and Systems Engineering
- Electrical and Electronic Engineering
- Mechanical Engineering
- Control and Optimization
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