Detection and Prognosis of Pulmonary Tuberculosis Using ML Classifiers with Soft Computing-Reference-Cited by-同舟云学术

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Detection and Prognosis of Pulmonary Tuberculosis Using ML Classifiers with Soft Computing

Published:2024-02-09 Issue: Volume:17 Page:1097-1101
ISSN:
Container-title:2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT)
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Author:

Bisht Girish Singh¹,Ganesh D²,Kumar Santosh³

Affiliation:

1. Tula's Institute,Department of Computer Science and Engineering,Dehradun,India

2. Jain (Deemed to be University),Department of Computer Science and Information Technology,Bangalore,India

3. Noida Institute of Engineering and Technology,Department of Internet of Things,Greater Noida,Uttar Pradesh,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10486056/10486063/10486406.pdf?arnumber=10486406

Reference41 articles.

1. An Improved Deep Network of Pulmonary Tuberculosis Lesions Detection based on YOLO

2. Detection of Pulmonary Tuberculosis Using Neural Network with Feature Extraction of Gray Level Run-Length Matrix Method on Lung X-Ray Images

3. AE-CNN Classification of Pulmonary Tuberculosis Based on CT Images

4. A CatBoost machine learning for prognosis of pathogen’s drug resistance in pulmonary tuberculosis

5. Tuberculosis diagnosis support analysis for precarious health information systems

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