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A Comparative Study of Convolutional Neural Network Architectures for Detecting Prostate Cancer

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Intelligent Computing and Optimization (ICO 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 1167))

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Abstract

One of the most prevalent common cancers among men is prostate cancer. Therefore, early detection is crucial for effective treatment. This study aims to detect prostate cancer using four Convolutional Neural Network (CNN) architectures. We evaluated our trained models and found a lower Root Mean Square Error (RMSE) of 2.9960 on the validation set indicating that our model can accurately detect prostate cancer in medical images. Our study suggests a promising prostate cancer detection model that could help improve patients’ early diagnosis and treatment outcomes.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, East West University, Dhaka, 1212, Bangladesh

    K. M. Safin Kamal, Mysha Maliha Priyanka, Alfe Suny, Maimuna Akter Liza, Sanjeda Sara Jennifer & Ahmed Wasif Reza

Authors
  1. K. M. Safin Kamal
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  2. Mysha Maliha Priyanka
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  3. Alfe Suny
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  4. Maimuna Akter Liza
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  5. Sanjeda Sara Jennifer
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  6. Ahmed Wasif Reza
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Corresponding author

Correspondence to Ahmed Wasif Reza .

Editor information

Editors and Affiliations

  1. Modeling Evolutionary Algorithms Simulation and Artificial Intelligence,, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Pandian Vasant

  2. Department of Theoretical and Applied Mechanics, Russian University of Transport, Moscow, Russia

    Vladimir Panchenko

  3. Statistics and Operations Research, North West University, Mmabatho, South Africa

    Elias Munapo

  4. Faculty of Engineering Management, Poznań University of Technology, Poznań, Poland

    Gerhard-Wilhelm Weber

  5. UOW Malaysia KDU Penang University College, Penang, Malaysia

    J. Joshua Thomas

  6. Department of Informatics Engineering, Petra Christian University, Surabaya, Indonesia

    Rolly Intan

  7. Department of Computer Science and Engineering, Chittagong University of Engineering and Technology (CUET), Chittagong, Bangladesh

    Mohammad Shamsul Arefin

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Kamal, K.M.S., Priyanka, M.M., Suny, A., Liza, M.A., Jennifer, S.S., Reza, A.W. (2024). A Comparative Study of Convolutional Neural Network Architectures for Detecting Prostate Cancer. In: Vasant, P., et al. Intelligent Computing and Optimization. ICO 2023. Lecture Notes in Networks and Systems, vol 1167. Springer, Cham. https://doi.org/10.1007/978-3-031-73318-5_1

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