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A trustworthy neural architecture search framework for pneumonia image classification utilizing blockchain technology

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A Correction to this article was published on 10 November 2023

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Abstract

A chest X-ray radiography is still the global standard for diagnosing pneumonia. Despite several studies, doctors still have trouble correctly diagnosing and classifying pneumonia. Neural architecture search (NAS) has the potential to enhance diagnostic efficiency and accuracy. However, NAS methods fail to account for the security of data sources, and the result of model prediction cannot be communicated safely and consistently. To tackle these issues, we propose a trustworthy NAS method for pneumonia image classification using blockchain technology, which provides secure, reliable, and high-performance model automatic search and efficient data prediction capabilities. By synergistically combining NAS with blockchain technology, we enhance the transparency and interpretability of NAS-driven image classification processes, thereby safeguarding the confidentiality and integrity of sensitive medical information. Moreover, our approach automates the model construction process for pneumonia image classification, markedly reducing the reliance on manual intervention. Experimental results demonstrate that our method achieves comparable performance to state-of-the-art methods for pneumonia image classification while ensuring security. This provides a new solution for promoting medical aided diagnosis.

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Funding

This work was supported by the Natural Science Foundation of Gansu Province, grant number No.22JR11RA042. We would like to thank the Editor-in-Chief for handling our paper. We would also like to thank the reviewers for their time and effort in providing constructive suggestions for our paper.

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Authors and Affiliations

  1. School of Information Science and Engineering, Lanzhou University, Lanzhou, 730000, Gansu, China

    Yi Yang, Jiaxuan Wei, Zhixuan Yu & Ruisheng Zhang

  2. Information Center, The First Hospital of Lanzhou University, Lanzhou, 730000, Gansu, China

    Zhixuan Yu

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YY was involved in development or design of methodology, designing computer programs, implementation of the computer code and supporting algorithms and preparation, creation and presentation of the published work, and specifically writing the initial draft. JW and ZY was involved in preparation, creation, and presentation of the published work by those from the original research group, specifically critical review, commentary, or revision. RZ was involved in oversight and leadership responsibility for the research activity planning and execution, including mentorship external to the core team.

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Correspondence to Jiaxuan Wei or Ruisheng Zhang.

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“The original online version of this article was revised: ” In this article the statement in the Funding information section was incorrectly given as '22JR1RA042' and should have read '22JR11RA042'. The original article has been corrected.

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Yang, Y., Wei, J., Yu, Z. et al. A trustworthy neural architecture search framework for pneumonia image classification utilizing blockchain technology. J Supercomput 80, 1694–1727 (2024). https://doi.org/10.1007/s11227-023-05541-4

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