Deep neural network architecture and applications in healthcare
- Title
- Deep neural network architecture and applications in healthcare
- Creator
- Unnisa S.; Vijayalakshmi A.; Jagun Z.T.
- Description
- Gaining insights related to medical data has always been a challenge, as limited technology delays treatment. Various types of data are collected from the medical field, such as sensor data, that are heterogeneous in nature. All of these are very poorly maintained and require more structuring. For this reason, deep learning is becoming more and more popular in this area. There are many challenges due to inadequate and irrelevant data. Insufficient domain knowledge also adds to the challenge. Modern deep learning models can help understand the dataset. This chapter provides an overview of deep learning, its various architectures, and convolutional neural networks. It also highlights how deep learning technologies can help advance healthcare. 2022 River Publishers.
- Source
- Deep Learning for Healthcare Decision Making, pp. 25-45.
- Date
- 2022-01-01
- Publisher
- River Publishers
- Coverage
- Unnisa S., Department of Computer Science, CHRIST (Deemed to be University), India; Vijayalakshmi A., Department of Computer Science, CHRIST (Deemed to be University), India; Jagun Z.T., Faculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Malaysia
- Rights
- Restricted Access
- Relation
- ISBN: 978-877022388-1; 978-877022389-8
- Format
- Online
- Language
- English
- Type
- Book chapter
Collection
Citation
Unnisa S.; Vijayalakshmi A.; Jagun Z.T., “Deep neural network architecture and applications in healthcare,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/18542.