Automated Leukaemia Prediction and Classification Using Deep Learning Techniques
- Title
- Automated Leukaemia Prediction and Classification Using Deep Learning Techniques
- Creator
- Narendran M.; Amarendra K.; Revathy D.; Divyapushpalakshmi M.; Sharma D.K.; Upreti K.
- Description
- Leukemia is typically diagnosed based on an abnormal blood count, frequently an elevated White Blood Cell (WBC) count. The diagnosis is established through bone marrow, replaced by neoplastic cells. Acute Lymphoblastic Leukemia (ALL) is a type of leukaemia that affects the blood and bone marrow. Leukaemia primarily affects children and adults around the world. Early leukaemia detection is critical for appropriately treating patients, especially children. This research aims to present a diagnostic method that uses computational intelligence and image processing algorithms to identify blast cells from ALL images. The medical image is prepared initially using the preprocessing and segmentation technique for efficient classification. In this research, the type is accomplished using Bidirectional Associative Memory Neural Networks (BAMNN), where the accuracy is 96.87%, the highest classification rate and outperforms the existing technique. 2023 IEEE.
- Source
- 2023 International Conference on Communication, Security and Artificial Intelligence, ICCSAI 2023, pp. 420-425.
- Date
- 2023-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- accuracy; activation function; and associative memory; bone marrow; classification; DL; Leukaemia; neural network; neurons
- Coverage
- Narendran M., Kcg College of Technology, Department of Information Technology, Tamil Nadu, Chennai, India; Amarendra K., Koneru Lakshmaiah Education Foundation, Department of Computer Science and Engineering, Andhra Pradesh, Vaddeswaram, 522502, India; Revathy D., Karpaga Vinayaga College of Engineering and Technology, Department of Computer Science and Engineering, Tamil Nadu, Chengalpet, India; Divyapushpalakshmi M., Gitam University, Department of Computer Science and Engineering, Bengaluru, 561203, India; Sharma D.K., Jaypee University of Engineering and Technology, Department of Mathematics, Madhya Pradesh, Guna, 473226, India; Upreti K., Christ (Deemed to Be University), Department of Computer Science, Delhi -NCR, Ghaziabad, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835036996-0
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Narendran M.; Amarendra K.; Revathy D.; Divyapushpalakshmi M.; Sharma D.K.; Upreti K., “Automated Leukaemia Prediction and Classification Using Deep Learning Techniques,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/19680.