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Abstract
Early stage of prediction and diagnosis is the only way to solve the challenges due to medical data. Machine learning tools and techniques help in prediction and diagnosis of different types of medical data. In this paper, Simplex Method based Social Spider Optimization (SMSSO) method is used which modifies the Social Spider Optimization (SSO) method. Different types of datasets were used to validate the SMSSO-NN technique. SMSSO-NN shows 99.36%, 94%, 95.78%, and 98% accuracy in Wisconsin Breast Cancer (WBC), Lung cancer, Diabetic, and Cervical cancer datasets, respectively that is better than other methods. The accuracy of the SMSSO-NN algorithm is associated with different classification techniques like Structured Singular Value (SSV), Local Linear Wavelet Neural Network-Firefly Algorithm (LLWNN-FA), and Rough Set Theory.
DISCLOSURE STATEMENT
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Monalisa Nayak
Monalisa Nayak completed her Master’s degree from S’O’A University. Currently, she is working as an assistant professor in the Department of Electronics & Communication Engineering, Indira Gandhi Institute of Technology, Sarang. Her area of research include soft computing, optimization techniques, big data and data mining. Email: [email protected]
Soumya Das
Soumya Das completed her Master's degree from IIIT Bhubaneswar. Currently, she is working as an assistant professor in the Department of Computer Science Engineering, Govt College of Engineering, Kalahandi, Her area of research include soft computing, optimization techniques, big data and data mining.
Urmila Bhanja
Urmila Bhanja received her PhD from the Dept of E & ECE, Indian Institute of Technology, Kharagpur, West Bengal, India in the year 2011. Currently, she is working as an associate professor in the Department of Electronics & Communication Engineering, Indira Gandhi Institute of Technology, Sarang, India. She has published many papers in reputed international journals and conferences. She is also a reviewer for many reputed international journals and conferences. Her area of research includes optical communication, optical network, wireless communication, wireless network, soft computing, optimization techniques, and big data. Email: [email protected]
Manas Ranjan Senapati
Manas Ranjan Senapati received his PhD from the Dept of CSE from BPUT. Currently, he is working as an associate professor in the Department of Computer Science Engineering, Veer Surendra Sai University of Technology, Burla. He has published many papers in reputed international journals and conferences. He is also a reviewer for many reputed international journals and conferences. His area of research includes, soft computing, optimization techniques, and big data, data mining, big data analysis, pattern analysis, clustering. Email: [email protected]