Accountable, Responsible, Transparent Artificial Intelligence in Ambient Intelligence Systems for Healthcare

Vourganas, I., Attar, H. and Michala, A. L. (2022) Accountable, Responsible, Transparent Artificial Intelligence in Ambient Intelligence Systems for Healthcare. In: Chakraborty, C. and Khosravi, M. R. (eds.) Intelligent Healthcare: Infrastructure, Algorithms and Management. Springer: Singapore, pp. 87-111. ISBN 9789811681493 (doi: 10.1007/978-981-16-8150-9_5)

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The future due to various socioeconomic reasons will demand an increased need for the extension of rehabilitation in home environments. However, due to the rapid development of the Ambient Intelligent (AmI) systems, various solutions through different approaches could solve problems which have concerned the health industry. However, AmI approaches due to complexity and multidisciplinarity should utilize the right tools in order to become a successful solution in the health sector. AmI consists of two main components. The hardware part which utilizes various sensors (wearable, ambient, contactless). This is combined with an AI part, which utilizes advanced Machine Learning algorithms. Successful AmI systems should follow various criteria. This chapter aims to review the required criteria for the integration of AmI into home-based health and care. A case study is reviewed, which combines and complies with several identified criteria. The system was tested with human subjects it was non-intrusive nor wearable, with a patient centric approach. The system demonstrated encouraging results with high accuracy. Moreover, Accountable, Reliable and Transparent AI was applied successfully to proact individualization and increase the level of trust. Although the AmI systems are promising, research is premature. More systematic research is needed for integration to the healthcare domain.

Item Type:Book Sections
Glasgow Author(s) Enlighten ID:Michala, Dr Lito
Authors: Vourganas, I., Attar, H., and Michala, A. L.
College/School:College of Science and Engineering > School of Computing Science
Published Online:03 June 2022
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