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Data classification using rough set and bioinspired computing in healthcare applications - an extensive review

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Abstract

The change in living standard made people to think on their physical health. Accordingly, healthcare organizations are concentrating more on physical health of people in terms of disease diagnosis and patient care. Digitization is a step towards this end. Nevertheless, digitization generates a voluminous of data every second. Besides, these data contain uncertainties and may be imprecise. Analyzing such uncertainties and impreciseness in an information system is a critical task. Computational intelligence techniques are developed to handle such cases. These techniques include fuzzy set, rough set, soft set, neutrosophic set, bio-inspired, nature-inspired, and evolutionary computing. This research paper presents an extensive review of healthcare that has been carried out by researchers using rough and bio-inspired computing. The purpose of this review is to provide an understanding of prevailing research and relevant information in disease diagnosis concerning rough set and bio-inspired computing. Besides, the application and future scope of research are also presented.

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Kumari, N., Acharjya, D.P. Data classification using rough set and bioinspired computing in healthcare applications - an extensive review. Multimed Tools Appl 82, 13479–13505 (2023). https://doi.org/10.1007/s11042-022-13776-1

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