Application of CNN and Recurrent Neural Network Method for Osteosarcoma Bone Cancer Detection
- Title
- Application of CNN and Recurrent Neural Network Method for Osteosarcoma Bone Cancer Detection
- Creator
- Nanthini S.; Sivabalan R.; Sivabalan S.; Bethapudi P.; Kukreti R.; Chauhan A.
- Description
- The outlook for people with metastatic osteosarcoma at an advanced stage is poor. Osteosarcoma is the most frequent form of bone cancer in children and young adults. There is an urgent need for both advances in treatment tactics and the identification of novel therapeutic targets for osteosarcoma since the disease typically develops resistance to existing treatments. Cancer stem cells, also known as tumor stem cells, have been linked to the development and spread of cancer at multiple points in the disease's progression. Cancer stem cells are linked to treatment resistance and carcinogenesis, and recent studies have demonstrated that osteosarcoma shares these properties. The proposed methodology rests on the three pillars of preprocessing, feature extraction, and model training. During preprocessing, that the proposed approach eliminated isolated highlights to help us zero in on the trustworthy region. They use the wavelet transform and the gray level co-occurrence matrix to extract features. A CNN-RNN technique is used to evaluate the models. In terms of output quality, the proposed technique is superior to both CNN and RNN. 2023 IEEE.
- Source
- International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, pp. 62-67.
- Date
- 2023-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Cancer Stem Cell (CSC); Convolutional Neural Network (CNN); Recurrent Neural Network (RNN)
- Coverage
- Nanthini S., Saveetha School of Engineering, Department of Data Science, Chennai, Thandalam, India; Sivabalan R., Sri Ramakrishna College of Engineering, Department of Cse, Tamilnadu, Perambalur, India; Sivabalan S., Sri Ramakrishna College of Engineering, Department of Cse, Tamilnadu, Perambalur, India; Bethapudi P., Cse, Gitam School of Technology, Gitam Deemed to Be University, Visakhapatnam, India; Kukreti R., Graphic Era Deemed to Be University, Department of Hospitality Management, Uttarakhand, Dehradun, India; Chauhan A., School of Sciences, Christ (Deemed to Be University), Department of Life Sciences, Karnataka, Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835030085-7
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Nanthini S.; Sivabalan R.; Sivabalan S.; Bethapudi P.; Kukreti R.; Chauhan A., “Application of CNN and Recurrent Neural Network Method for Osteosarcoma Bone Cancer Detection,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/19775.