Prediction of Thyroid Classes Using Feature Selection of AEHOA Based CNN Model for Healthy Lifestyle

Authors

Rachappa Jopate, Department of Information Technology, University of Technology and Applied Sciences, Al Mussanah, Oman.Follow
Piyush Kumar Pareek, Department of AI ML, NITTE Meenakshi Institute of Technology, Bangalore, India.Follow
DivyaJyothi M. G, Department of Information Technology, University of Technology and Applied Sciences, Al Mussanah, Oman.Follow
Ariam Saleh Zuwayid Juma Al Hasani, Department of Information Technology, University of Technology and Applied Sciences, Al Mussanah, Oman.Follow

Abstract

People with underactive thyroids frequently endure severe symptoms. Correct classification and machine learning substantially improve thyroid disease diagnosis. This precise classification will impact the timely delivery of care to the patients. Although diagnostic techniques exist, they frequently seek binary categorization, use insufficiently big datasets, and lack confirmation of their conclusions. The focus of current approaches is on model optimisation, whereas feature engineering is neglected. This research presents the Adaptive Elephant Herd Optimisation Algorithm (AEHOA) model for selecting optimal attributes in order to circumvent these limitations. At first, employ a method called the Synthetic Minority Over-sampling Technique (SMOTE) to even out the data. Finally, the parameters of the AEHOA model are fed into a Convolutional Neural Network (CNN) to categorise data and enhance prediction. The accuracy of classification predictions was also increased by tweaking the dataset. Both datasets were put through a categorization process for a more precise comparison of results.

Keywords

Adaptive Elephant Herd Optimization Algorithm, Convolutional Neural Network, Hyperthyroidism Imbalanced data, Machine Learning, Synthetic Minority Over-sampling Technique

Article Type

Special Issue Article

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite this Article

Jopate, Rachappa; Pareek, Piyush Kumar; G, DivyaJyothi M.; and Al Hasani, Ariam Saleh Zuwayid Juma (2024) "Prediction of Thyroid Classes Using Feature Selection of AEHOA Based CNN Model for Healthy Lifestyle," Baghdad Science Journal: Vol. 21: Iss. 5, Article 29.
DOI: https://doi.org/10.21123/bsj.2024.10547