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A Novel Security Model for Healthcare Prediction by Using DL

  • Conference paper
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Cryptology and Network Security with Machine Learning (ICCNSML 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 918))

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Abstract

Predictive models are employed in order to forecast forthcoming events of which knowledge is now lacking. This is achieved by analysing a collection of pertinent predictors or variables, taking into account both contemporary and past data. Predictive modelling, alternatively referred to as predictive analytics, encompasses the utilization of statistical methodologies, data mining techniques, and artificial intelligence approaches to address a diverse range of applications. In the field of healthcare, a predictive model is utilized to acquire knowledge from past patient data in order to forecast future medical issues and subsequently select the most appropriate course of therapy. This review emphasizes the application of deep learning (DL) models, including LSTM-Bi-LSTM, RNN, CNN, RBM, and GRU, in various healthcare contexts. The findings suggest that the LSTM/Bi-LSTM model is commonly employed in the analysis of time-series medical data, whereas CNN is frequently utilized for the examination of medical picture data. The utilization of a model based on deep learning has the potential to support healthcare personnel in expediting decision-making processes pertaining to prescriptions and hospitalizations, resulting in time savings and enhanced service provision within the healthcare business; especially for COVID-19 case, this model can be used which makes it better suitable for examining medical images. The present study examines the many prediction models employed in healthcare applications through the utilization of deep learning techniques and also makes sure that the extracted dataset is secured while processing it.

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Authors and Affiliations

  1. Moscow Institute of Physics and Technology, 9 Institytskiy Per., Dolgoprudny, Moscow Region, Russia

    Anshita Dhoot

  2. JIMS Engineering Management Technical Campus, 48/4, Knowledge Park III, Greater Noida, India

    Rahul Deva

  3. Pranveer Institute of Engineering and Technology, Kanpur, NH19, India

    Varun Shukla

Authors
  1. Anshita Dhoot
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  2. Rahul Deva
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  3. Varun Shukla
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Corresponding author

Correspondence to Anshita Dhoot .

Editor information

Editors and Affiliations

  1. Department of Mathematics, Pranveer Singh Institute of Technology, Kanpur, India

    Atul Chaturvedi

  2. Department of Mathematics, Indian Institute of Technology Jammu, Jammu, India

    Sartaj Ul Hasan

  3. Applied Statistics Unit, Indian Statistical Institute, Kolkata, India

    Bimal Kumar Roy

  4. Department of Mathematics, Bar-Ilan University, Ramat-Gan, Israel

    Boaz Tsaban

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

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Dhoot, A., Deva, R., Shukla, V. (2024). A Novel Security Model for Healthcare Prediction by Using DL. In: Chaturvedi, A., Hasan, S.U., Roy, B.K., Tsaban, B. (eds) Cryptology and Network Security with Machine Learning. ICCNSML 2023. Lecture Notes in Networks and Systems, vol 918. Springer, Singapore. https://doi.org/10.1007/978-981-97-0641-9_53

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  • DOI: https://doi.org/10.1007/978-981-97-0641-9_53

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-0640-2

  • Online ISBN: 978-981-97-0641-9

  • eBook Packages: EngineeringEngineering (R0)

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