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Modified MobileNet for Patient Survival Prediction

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Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (BrainLes 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12659))

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Abstract

Glioblastoma is a type of malignant tumor that varies significantly in size, shape, and location. The study of this type of tumor, one of which is about predicting the patient’s survival ability, is beneficial for the treatment of patients. However, the supporting data for the survival prediction model are minimal, so the best methods are needed for handling it. In this study, we propose an architecture for predicting patient survival using MobileNet combined with a linear survival prediction model (SPM). Several variations of MobileNet are tested to obtain the best results. Variations tested include modification of MobileNet V1 with freeze or unfreeze layers, and modification of MobileNet V2 with freeze or unfreeze layers connected to SPM. The dataset used for the trial came from BraTS 2020. A modification based on the MobileNet V2 architecture with the freezing layer was selected from the test results. The results of testing this proposed architecture with 95 training data and 23 validation data resulted in an MSE Loss of 78374.17. The online test results with the validation dataset 29 resulted in an MSE loss value of 149764.866 with an accuracy of 0.345. Testing with the testing dataset resulted in increased accuracy of 0.402. These results are promising for better architectural development.

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Acknowledgements

This research was supported by the Ministry of Education and Culture and the Ministry of Research and Technology/BRIN, Indonesia. We are deeply grateful for both the Beasiswa Pendidikan Pascasarjana Dalam Negeri(BPPDN) and Penelitian Disertasi Doktor(PDD) 2020–2021 grant, which enabled this research to be carried out.

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Authors and Affiliations

  1. Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia

    Agus Subhan Akbar, Chastine Fatichah & Nanik Suciati

  2. Universitas Islam Nahdlatul Ulama Jepara, Jepara, Indonesia

    Agus Subhan Akbar

Authors
  1. Agus Subhan Akbar
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  2. Chastine Fatichah
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  3. Nanik Suciati
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Correspondence to Agus Subhan Akbar .

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Editors and Affiliations

  1. University of Zurich, Zurich, Switzerland

    Alessandro Crimi

  2. University of Pennsylvania, Philadelphia, PA, USA

    Spyridon Bakas

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Akbar, A.S., Fatichah, C., Suciati, N. (2021). Modified MobileNet for Patient Survival Prediction. In: Crimi, A., Bakas, S. (eds) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2020. Lecture Notes in Computer Science(), vol 12659. Springer, Cham. https://doi.org/10.1007/978-3-030-72087-2_33

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  • DOI: https://doi.org/10.1007/978-3-030-72087-2_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-72086-5

  • Online ISBN: 978-3-030-72087-2

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