Article: Identification of AIDS disease severity based on computational intelligence techniques using clonal selection algorithm Journal: International Journal of Convergence Computing (IJCONVC) 2016 Vol.2 No.3/4 pp.193 - 207 Abstract: The mining bioinformatics data is a newly formed area in the process between bioinformatics and data mining. The process of developing the algorithms manipulated is based on computational intelligence. The agitation cases are created everywhere in the world concerning the Acquired Immunodeficiency Syndrome (AIDS) disease which are complex. Data were collected throughout self-administered mail survey nationwide at clinical and drug treatment centres and AIDS service organisations. Every country is facing the problem about AIDS occurring at a time immediately before the present survey according to the World Health Organization (WHO), especially that causing the death of many CD4 count cells. This paper identifies patients' severity and it is useful to doctors. This research identifies patients' severity and it is useful to doctors. In this paper in detail of machine learning algorithm of the clonal selection algorithm more effective diagnosis and optimise the data of AIDS disease. Those techniques achieved promising results. Inderscience Publishers - linking academia, business and industry through research

Title: Identification of AIDS disease severity based on computational intelligence techniques using clonal selection algorithm

Authors: Dharmaiah Devarapalli; Panigrahi Srikanth; MandaRam Narasinga Rao; J. Venkata Rao

Addresses: Department of Information Technology, Shri Vishnu Engineering College for Women, Bhimavaram-534202, A.P., India ' Department of Information Technology, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad – 500090, India ' Department of Computer Science and Engineering, KL University, Vaddeswaram, Guntur District, A.P., 522 502, India ' Department of Information Technology, Shri Vishnu Engineering College for Women, Bhimavaram, A.P., 534202, India

Abstract: The mining bioinformatics data is a newly formed area in the process between bioinformatics and data mining. The process of developing the algorithms manipulated is based on computational intelligence. The agitation cases are created everywhere in the world concerning the Acquired Immunodeficiency Syndrome (AIDS) disease which are complex. Data were collected throughout self-administered mail survey nationwide at clinical and drug treatment centres and AIDS service organisations. Every country is facing the problem about AIDS occurring at a time immediately before the present survey according to the World Health Organization (WHO), especially that causing the death of many CD4 count cells. This paper identifies patients' severity and it is useful to doctors. This research identifies patients' severity and it is useful to doctors. In this paper in detail of machine learning algorithm of the clonal selection algorithm more effective diagnosis and optimise the data of AIDS disease. Those techniques achieved promising results.

Keywords: AIDS data; CD4 cells count; fitness function; intelligence technique; clonal selection algorithm.

DOI: 10.1504/IJCONVC.2016.090084

International Journal of Convergence Computing, 2016 Vol.2 No.3/4, pp.193 - 207

Received: 27 Jan 2016
Accepted: 09 Jan 2017
Published online: 28 Feb 2018 *

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Title: Identification of AIDS disease severity based on computational intelligence techniques using clonal selection algorithm

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