Open Access

ARTICLE

Cat and Mouse Optimizer with Artificial Intelligence Enabled Biomedical Data Classification

B. Kalpana¹, S. Dhanasekaran², T. Abirami³, Ashit Kumar Dutta⁴, Marwa Obayya⁵, Jaber S. Alzahrani⁶, Manar Ahmed Hamza^7,*

1 Department of Information Technology, RMD Engineering College, Chennai, 601206, India
2 Department of Information Technology, Kalasalingam Academy of Research and Education, Srivilliputtur, 626126, India
3 Department of Information Technology, Kongu Engineering College, Erode, 638060, India
4 Department of Computer Science and Information Systems, College of Applied Sciences, AlMaarefa University, Ad Diriyah, Riyadh, 13713, Kingdom of Saudi Arabia
5 Department of Biomedical Engineering, College of Engineering, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia
6 Department of Industrial Engineering, College of Engineering at Alqunfudah, Umm Al-Qura University, Saudi Arabia
7 Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, AlKharj, Saudi Arabia

* Corresponding Author: Manar Ahmed Hamza. Email:

Computer Systems Science and Engineering 2023, 44(3), 2243-2257. https://doi.org/10.32604/csse.2023.027129

Received 11 January 2022; Accepted 11 March 2022; Issue published 01 August 2022

Abstract

Biomedical data classification has become a hot research topic in recent years, thanks to the latest technological advancements made in healthcare. Biomedical data is usually examined by physicians for decision making process in patient treatment. Since manual diagnosis is a tedious and time consuming task, numerous automated models, using Artificial Intelligence (AI) techniques, have been presented so far. With this motivation, the current research work presents a novel Biomedical Data Classification using Cat and Mouse Based Optimizer with AI (BDC-CMBOAI) technique. The aim of the proposed BDC-CMBOAI technique is to determine the occurrence of diseases using biomedical data. Besides, the proposed BDC-CMBOAI technique involves the design of Cat and Mouse Optimizer-based Feature Selection (CMBO-FS) technique to derive a useful subset of features. In addition, Ridge Regression (RR) model is also utilized as a classifier to identify the existence of disease. The novelty of the current work is its designing of CMBO-FS model for data classification. Moreover, CMBO-FS technique is used to get rid of unwanted features and boosts the classification accuracy. The results of the experimental analysis accomplished by BDC-CMBOAI technique on benchmark medical dataset established the supremacy of the proposed technique under different evaluation measures.

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Keywords

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