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Exploration of Deep Neural Networks and Effect of Optimizer for Pulmonary Disease Diagnosis

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Abstract

According to recent statistics, Tuberculosis and pneumonia are among the top 10 fatal diseases globally. Researchers found that patients with both COVID-19 and Tuberculosis (COVID-TB) were more likely to develop a severe illness or die than patients with just one disease. According to the World Health Organization, COVID-19 has killed 5.91 million people so far, and the number continues to rise. India and the United States together account for 1.44 million deaths or 24.4% of the total. Pneumonia has killed 2.5 million people globally, 75% of whom are under 5 or over 70 years. According to the 2020 mortality report, TB is the 13th leading cause of death in the world, with 1.5 million deaths. Of these, most deaths are in India, followed by China. Looking at the statistics, we have contributed our research models which can help in the early detection of such fatal diseases using CNN models. Our experimental results would assist doctors to anticipate the illness more precisely and will offer assistance to the conventional techniques. Our experiment comprises a total of 28 models comprising 14 transfer learning and 14 proposed CNN-based models. We have compared the models based on their accuracy, Recall factor, training time, etc. Models are trained with combinations of architectures with Adam and RMSProp optimizers. From the experimental results, ResNet152V2 architecture performed best with an accuracy of 93% followed by A8 and ResNet101V2 architecture having 91.96%. Furthermore, the R1 model was found to be the best model when considering OF-Score.

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Authors and Affiliations

  1. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Rakshit Agrawal, Hrishita Sarkar, Abhisek Omkar Prasad & Abhaya Kumar Sahoo

  2. Department of CSE and IT, Jaypee Institute of Information Technology University, Delhi, India

    Ankit Vidyarthi

  3. School of Computer Applications, KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Rabindra Kumar Barik

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  1. Rakshit Agrawal
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  4. Abhaya Kumar Sahoo
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Correspondence to Abhaya Kumar Sahoo.

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This article is part of the topical collection “Research Trends in Computational Intelligence” guest edited by Anshul Verma, Pradeepika Verma, Vivek Kumar Singh and S. Karthikeyan.

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Agrawal, R., Sarkar, H., Prasad, A.O. et al. Exploration of Deep Neural Networks and Effect of Optimizer for Pulmonary Disease Diagnosis. SN COMPUT. SCI. 4, 471 (2023). https://doi.org/10.1007/s42979-023-01940-9

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