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Deep Learning in Healthcare

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Deep Learning in Data Analytics

Part of the book series: Studies in Big Data ((SBD,volume 91))

Abstract

Machine learning is quickly becoming an important tool for diagnosis and prognosis of various medical conditions. Complex input output mappings are dealt in deep learning, which is developed based on machine learning approach. Due to its efficiency and similarity to the working of the human brain, deep neural networks are a preferred method of processing and analysing medical data. In addition to diagnosis, deep learning is used to study the progression of disease, develop a personalised treatment plan and for overall patient management. This chapter discusses the architecture and working of deep neural networks and focus on its application in the detection and treatment of various diseases like cancer, diabetes, Alzheimer’s and Parkinson’s disease.

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Author information

Authors and Affiliations

  1. SCOPE, VIT, Vellore, 632014, Tamil Nadu, India

    Deeksha Kaul & Harika Raju

  2. SITE, VIT, Vellore, 632014, Tamil Nadu, India

    B. K. Tripathy

Authors
  1. Deeksha Kaul
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  2. Harika Raju
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  3. B. K. Tripathy
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Corresponding author

Correspondence to B. K. Tripathy .

Editor information

Editors and Affiliations

  1. School of Computing Science and Engineering, VIT University, Vellore, India

    Debi Prasanna Acharjya

  2. Department of Computer Science Engineering, Amity University Kolkata, Kolkata, India

    Anirban Mitra

  3. School of Computer Science and Engineering, Taylor's University, Subang Jaya, Malaysia

    Noor Zaman

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Kaul, D., Raju, H., Tripathy, B.K. (2022). Deep Learning in Healthcare. In: Acharjya, D.P., Mitra, A., Zaman, N. (eds) Deep Learning in Data Analytics. Studies in Big Data, vol 91. Springer, Cham. https://doi.org/10.1007/978-3-030-75855-4_6

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