A Body Area Network Approach for Stroke-Related Disease Diagnosis Using Artificial Intelligence with Deep Learning Techniques-Reference-Cited by-同舟云学术

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A Body Area Network Approach for Stroke-Related Disease Diagnosis Using Artificial Intelligence with Deep Learning Techniques

Published:2022 Issue: Volume: Page:243-256
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
Short-container-title:

Author:

Kumar M. Anand,Kumar A. Suresh

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-12638-3_21

Reference25 articles.

1. Liu, Q., Mkongwa, K.G., Zhang, C.: Performance issues in wireless body area networks for the healthcare application. A survey and future prospects. SN Appl. Sci. 155–158 (2021)

2. Salam, H.A., Khan, B.M.: Use of wireless system in healthcare for developing countries. Digit. Commun. Netw. 2(1), 35–46 (2016)

3. Movassaghi, S., Abolhasan, M., Lipman, J., Smith, D., Pour, A.J.: Wireless body area networks. A survey. IEEE Commun. Surv. Tutor. 16(3), 1658–1686 (2014)

4. Fang, G., Xu, P., Liu, W.: Automated ischemic stroke subtyping based on machine learning approach. IEEE Access 8, 118426–118432 (2020)

5. Kim, A.S., Cahill, E., Cheng, N.T.: Global stroke belt. Geographic variation in stroke burden worldwide. Stroke 46(12), 3564–3570 (2015)

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