Attention-Based CNN Model for Burn Severity Assessment-Reference-Cited by-同舟云学术

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Attention-Based CNN Model for Burn Severity Assessment

Published:2023-10-15 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)
language:
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Author:

Rahman Saeka¹,Faezipour Miad²,Ribeiro Guilherme Aramizo¹,Ridelman Elika³,Klein Justin D.³,Angst Beth A.³,Shanti Christina M.³,Rastgaar Mo⁴

Affiliation:

1. Purdue University, School of Engineering Technology,West Lafayette,IN,USA,47907

2. Purdue University,School of Engineering Technology,West Lafayette,IN,USA,47907

3. Children’s Hospital of Michigan/Wayne State University,Division of Pediatric Surgery,The Department of Surgery,Detroit,MI,USA

4. School of Engineering Technology, Purdue University, West Lafayette, IN 47907, USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10313339/10313352/10313435.pdf?arnumber=10313435

Reference13 articles.

1. A comparative study of the classification of skin burn depth in human;Kuan;Journal of Telecommunication, Electronic and Computer Engineering (JTEC),2017

2. Does the estimation of burn extent at admission differ from the assessment at discharge?

3. Changing the Way We Think About Burn Size Estimation

4. The use of telemedicine in burn care: development of a mobile system for TBSA documentation and remote assessment;Parvizi;Annals of burns and fire disasters,2014

5. A Framework for Automatic Burn Image Segmentation and Burn Depth Diagnosis Using Deep Learning

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