Optimisation algorithm in health care: review on the State-of-the-Art models

Abstract

Humans are affected by some diseases due to ageing, which raises the necessity of effective healthcare operation schemes. Such techniques are necessary to provide efficiently and cost-effectively service to patients at the proper time. The huge knowledge required to process the HC application is obtained from the developed HC technologies. Research has recently shown that artificial intelligence (AI) can facilitate extraordinary performance for various HC applications. However, recently different metaheuristic-based optimisation algorithms have been developed to improve AI-based HC techniques' performance. Therefore, this review discusses different HC models that leverage the benefits of metaheuristic algorithms to achieve better performance. The major goal of this review is to support the researchers seeking a better reference to develop secure and smarter metaheuristic-based HC models. These models are efficient in reducing system complexity by improving efficiency. But in the future, many openings are available to meet such requirements efficient techniques that satisfy all the existing challenges. This developed review has surveyed and summarised different challenges and future directions to understand the available challenges. This research reviews various journal publications based on the metaheuristic approach.es from the recent papers available in standard journals from 2015 to 2021.

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