Improving Early Detection and Classification of Lung Diseases With Innovative MobileNetV2 Framework-Reference-Cited by-同舟云学术

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Improving Early Detection and Classification of Lung Diseases With Innovative MobileNetV2 Framework

Published:2024 Issue: Volume:12 Page:116202-116217
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Tripathi Amrita¹,Singh Tripty¹^ORCID,Nair Rekha R.²^ORCID,Duraisamy Prakash³

Affiliation:

1. Department of Computer Science and Engineering, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Bengaluru, India

2. Department of Computer Science and Engineering, Alliance School of Advanced Computing, Alliance University, Bengaluru, India

3. Department of Computer Science, University of Wisconsin-Green Bay, Green Bay, WI, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10630783.pdf?arnumber=10630783

Reference60 articles.

1. LungNet22: A Fine-Tuned Model for Multiclass Classification and Prediction of Lung Disease Using X-ray Images

2. Automatic lung disease classification from the chest X-ray images using hybrid deep learning algorithm

3. The role of artificial intelligence in healthcare: a structured literature review

4. Previous Lung Diseases and Lung Cancer Risk: A Systematic Review and Meta-Analysis

5. Computed tomography and patient risk: Facts, perceptions and uncertainties

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