A novel lightweight deep learning based approaches for the automatic diagnosis of gastrointestinal disease using image processing and knowledge distillation techniques.

Journal: Computer methods and programs in biomedicine
PMID: 39798279

Abstract

BACKGROUND: Gastrointestinal (GI) diseases pose significant challenges for healthcare systems, largely due to the complexities involved in their detection and treatment. Despite the advancements in deep neural networks, their high computational demands hinder their practical use in clinical environments.

Authors

  • Zafran Waheed
    School of Computer Science and Engineering, Central South University, China. Electronic address: zafranwaheed@csu.edu.cn.
  • Jinsong Gui
    School of Electronic Information, Central South University, China. Electronic address: jsgui06@163.com.
  • Md Belal Bin Heyat
    CenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake University, Hangzhou, Zhejiang, China.
  • Saba Parveen
    College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China.
  • Mohd Ammar Bin Hayat
    College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China.
  • Muhammad Shahid Iqbal
    Department of Clinical Pharmacy, College of Pharmacy, Prince Sattam bin Abdulaziz University, Alkharj, Kingdom of Saudi Arabia.
  • Zouheir Aya
    College of Mechanical Engineering, Changsha University of Science and Technology, Changsha, Hunan, China.
  • Awais Khan Nawabi
    School of Computer Science and Engineering, University of Central South University, Hunan, China.
  • Mohamad Sawan
    CenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake University, Hangzhou, China.

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