Abstract
Medical diagnosis is the key prerequisite for any medical treatment. To get that optimized result of any diagnosis, several tests have been proposed in a cost and time-effective manner. Metaheuristic algorithms are used in many fields; especially in medical science, it has a huge impact. With the help of these algorithms, many models have been developed to get accurate results during diagnosis. In this paper, we are elaborating on the Genetic Algorithm (GA). It is a well-known metaheuristic algorithm. We categorically represent the GA applications in medical science. The genetic algorithm finds its way in different fields of medical science like Cancer Treatment, Image Segmentation, Gynecology and Obstetrics, Cardiology, Personalized Health Care, Plastic Surgery, Disease Diagnosis, Radiology, Radiotherapy, and Diabetes Prediction. We discuss how the genetic algorithm principle is successfully applied in these applications. We also try to make a comparative discussion among the selected applications on different parameters like diagnosis time, cost, and many more in a lucid manner and find the research gaps.
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Karmakar, R. (2022). Application of Genetic Algorithm (GA) in Medical Science: A Review. In: Luhach, A.K., Poonia, R.C., Gao, XZ., Singh Jat, D. (eds) Second International Conference on Sustainable Technologies for Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1235. Springer, Singapore. https://doi.org/10.1007/978-981-16-4641-6_8
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