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Survival Modeling of Disease Consequences and Post-disease Syndromes

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Proceedings of 2023 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2023) (MICAD 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1166))

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Abstract

We present a survival model for human maladies, which leave victims with permanent health damages requiring life-long medical observation and treatment. The model allows national health authorities to prepare sufficient medical specialists with adequate capacity in specialized clinics, vaccinations, spas, or rehabilitation facilities. We test the model on Czech Polio (Poliomyelitis Anterior Acuta) victims’ data. COVID-19 or Long Covid-19 and the treatment of their wide range of ongoing health problems, where these conditions can last weeks, months, or years, can benefit from Polio and COVID-19 RNA virus similarities.

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Author information

Authors and Affiliations

  1. Institute of Information Theory and Automation, Czech Academy of Sciences, Pod Vodárenskou věží 4, 182 08, Prague, Czechia

    Michal Haindl

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  1. Michal Haindl
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Correspondence to Michal Haindl .

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Editors and Affiliations

  1. Department of Computer Science, Shanghai Jiao Tong University, Shanghai, China

    Ruidan Su

  2. Department of Informatics, University of Leicester, Leicester, UK

    Yu-Dong Zhang

  3. University of Manchester, Manchester, UK

    Alejandro F. Frangi

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Haindl, M. (2024). Survival Modeling of Disease Consequences and Post-disease Syndromes. In: Su, R., Zhang, YD., Frangi, A.F. (eds) Proceedings of 2023 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2023). MICAD 2023. Lecture Notes in Electrical Engineering, vol 1166. Springer, Singapore. https://doi.org/10.1007/978-981-97-1335-6_32

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  • DOI: https://doi.org/10.1007/978-981-97-1335-6_32

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-1334-9

  • Online ISBN: 978-981-97-1335-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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