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Artificial Intelligence, Machine Learning and Reasoning in Health Informatics—Case Studies

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Book cover Signal Processing Techniques for Computational Health Informatics

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 192))

Abstract

To apply Artificial Intelligence (AI), Machine Learning (ML) and Machine Reasoning (MR) in health informatics are often challenging as they comprise with multivariate information coming from heterogeneous sources e.g. sensor signals, text, etc. This book chapter presents the research development of AI, ML and MR as applications in health informatics. Five case studies on health informatics have been discussed and presented as (1) advanced Parkinson’s disease, (2) stress management, (3) postoperative pain treatment, (4) driver monitoring, and (5) remote health monitoring. Here, the challenges, solutions, models, results, limitations are discussed with future wishes.

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Notes

  1. 1.

    http://ecareathome.se/.

  2. 2.

    http://www.es.mdh.se/projects/324-ESS_H___Embedded_Sensor_Systems_for_Health_Research_Profile.

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Acknowledgements

The authors would like to acknowledge the projects named ESS-H: Embedded Sensor Systems for Health Research Profile is funded by Knowledge Foundation and SAAPHO: Secure Active Aging: Participation and Health for the Old (aal-2010-3-035) is funded by the Call AAL (Ambient Assisted Living) within the Call 3. Authors would also like to acknowledge the Swedish Governmental Agency for Innovation Systems (VINNOVA), Volvo Car Corporation, and VTI for financing the Vehicle Driver Monitoring (VDM) project. Authors also acknowledge the funding agency KKS and project partners for the IMod and the SafeDriver project.

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  1. School of Innovation, Design and Engineering, Mälardalen University, Västerås, Sweden

    Mobyen Uddin Ahmed, Shaibal Barua & Shahina Begum

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  1. Department of Electrical and Electronic Engineering, University of Dhaka, Dhaka, Bangladesh

    Md Atiqur Rahman Ahad

  2. Department of Electrical and Electronic Engineering, University of Dhaka, Dhaka, Bangladesh

    Mosabber Uddin Ahmed

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Ahmed, M.U., Barua, S., Begum, S. (2021). Artificial Intelligence, Machine Learning and Reasoning in Health Informatics—Case Studies. In: Ahad, M.A.R., Ahmed, M.U. (eds) Signal Processing Techniques for Computational Health Informatics. Intelligent Systems Reference Library, vol 192. Springer, Cham. https://doi.org/10.1007/978-3-030-54932-9_12

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