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Machine Learning Techniques for Big Data Analytics in Healthcare: Current Scenario and Future Prospects

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Telemedicine: The Computer Transformation of Healthcare

Part of the book series: TELe-Health ((TEHE))

Abstract

Big data analytics (BDA) using machine learning play an important role to drive actionable insights from a huge volume of data for different organizations, especially healthcare. The healthcare industry’s data is growing significantly due to the advancement of technology. It becomes a challenging task to acquire, store, analyze, and visualize healthcare data mainly due to the diversity of data sources like clinical records, electronic health records, sensing data, social media data, medical image data, omics data, etc. The complexity and heterogeneity of healthcare data entails proper management and analytical procedures to provide better solutions to real-world healthcare problems. In this chapter, various platforms that can handle healthcare data along with different algorithms based on machine learning (ML) techniques have been discussed. The chapter reviews different big data lifecycle challenges like storage, processing, data sharing, security, privacy, etc. The study also presents and implements a framework for big data analytics that can be explored for real-time disease prediction showcasing diabetes. This model can also be validated over different diseases like cancer detection, heart disease prediction, Alzheimer’s detection, etc. which share a commonality of data with diabetes, as in our case.

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Authors and Affiliations

  1. BGSB University, Rajouri, Jammu and Kashmir, India

    Shahid Mohammad Ganie, Majid Bashir Malik & Tasleem Arif

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  1. Shahid Mohammad Ganie
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  2. Majid Bashir Malik
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  3. Tasleem Arif
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Correspondence to Majid Bashir Malik .

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Editors and Affiliations

  1. School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun, Uttarakhand, India

    Tanupriya Choudhury

  2. School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun, Uttarakhand, India

    Avita Katal

  3. Department of Geography, Kyungpook National University, College of Social Sciences, Daegu, Korea (Republic of)

    Jung-Sup Um

  4. Amity University, Uttar Pradesh, India

    Ajay Rana

  5. Vice President for Research and Innovation, American University in the Emirates, Dubai International Academic City, Dubai, United Arab Emirates

    Marwan Al-Akaidi

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Ganie, S.M., Malik, M.B., Arif, T. (2022). Machine Learning Techniques for Big Data Analytics in Healthcare: Current Scenario and Future Prospects. In: Choudhury, T., Katal, A., Um, JS., Rana, A., Al-Akaidi, M. (eds) Telemedicine: The Computer Transformation of Healthcare. TELe-Health. Springer, Cham. https://doi.org/10.1007/978-3-030-99457-0_6

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