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Artificial Intelligence and Machine Learning for Health Risks Prediction

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Enhanced Telemedicine and e-Health

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 410))

Abstract

The emergence of the fourth industrial revolution has brought about the drive towards integrating technologies, such as machine learning, into healthcare solutions. This chapter explores how applications of machine learning in the healthcare sector have sought progress, and extricate the challenges with respect to early prediction of chronic illnesses. The review of past work in this fast-growing research and development area, as well as the state-of-the-art, is conducted in order to establish a roadmap for future trajectories. This study emphasises that there is no ML algorithm that can guarantee a reliable predictive outcome for all kinds of diseases in every given problem case, the quantity of the dataset employed has a significant contribution to the performance of the predictive algorithms, and that quality time must be given to the data preparation stages because the result of the ML algorithms employed depends on the quality of the dataset used. This work is mainly intended to serve researchers and developers in the field. The readership will also extend to practitioners and policy-makers.

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Authors and Affiliations

  1. Institute of Intelligent Systems, University of Johannesburg, Johannesburg, South Africa

    Luke Oluwaseye Joel, Wesley Doorsamy & Babu Sena Paul

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  1. Luke Oluwaseye Joel
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  2. Wesley Doorsamy
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  3. Babu Sena Paul
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Correspondence to Wesley Doorsamy .

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Editors and Affiliations

  1. Polytechnic of Coimbra, ESTGOH, Rua General Santos Costa, Oliveira do Hospital, Coimbra, Portugal

    Gonçalo Marques

  2. Department of Electrical and Electronics Engineering, Sikkim Manipal Institute of Technology, Majhitar, Sikkim, India

    Akash Kumar Bhoi

  3. University of Valladolid, Valladolid, Spain

    Isabel de la Torre Díez

  4. Universidad de Deusto, Bilbao, Vizcaya, Spain

    Begonya Garcia-Zapirain

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Joel, L.O., Doorsamy, W., Paul, B.S. (2021). Artificial Intelligence and Machine Learning for Health Risks Prediction. In: Marques, G., Kumar Bhoi, A., de la Torre Díez, I., Garcia-Zapirain, B. (eds) Enhanced Telemedicine and e-Health. Studies in Fuzziness and Soft Computing, vol 410. Springer, Cham. https://doi.org/10.1007/978-3-030-70111-6_12

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