(Received: 13-Dec.-2021, Revised: 24-Jan.-2022 , Accepted: 13-Feb.-2022)
In the field of medicine, there is a need to filter data to find information that is relevant for specific research problems. However, in the realm of scientific study, the process of selecting the appropriate data or features is a substantial and challenging problem. Therefore, in this paper, two wrapper feature selection (FS) methods based on novel metaheuristic algorithms named the arithmetic optimization algorithm (AOA) and the great deluge algorithm (GDA) were used to attempt to tackle the medical diagnostics challenge. Two methods, AOA and AOA-GD were tested on 23 medical benchmark datasets. According to all of the experimental data, the hybridization of the GDA with the AOA considerably increased the AOA’s search capability. The AOA-GD method was then compared with two previous wrapper FS approaches; namely, the coronavirus herd immunity optimizer with greedy crossover operator (CHIO-GC) and the binary moth flame optimization with Lévy flight (LBMFO_V3). When applied to the 23 medical benchmark datasets, the AOA-GD achieved an accuracy rate of 0.80, thereby surpassing both the CHIO-GC and LBMFO V3.

[1] M. Alweshah, S. A. Khalaileh, B. B. Gupta, A. Almomani, A. I. Hammouri and M. A. Al-Betar, "The Monarch Butterfly Optimization Algorithm for Solving Feature Selection Problems," Neural Computing and Applications, vol. 2020, pp. 1-15, 2020.

[2] C. Lam, A. Siefkas, N. S. Zelin et al., "Machine Learning As a Precision-medicine Approach to Prescribing COVID-19 Pharmacotherapy with Remdesivir or Corticosteroids," Clinical Therapeutics, vol. 43, no. 5, pp. 871-885, 2021.

[3] M. Alweshah, M. Al-Sendah, O. M. Dorgham, A. Al-Momani and S. Tedmori, "Improved Water Cycle Algorithm with Probabilistic Neural Network to Solve Classification Problems," Cluster Computing, vol. 23, pp. 2703-2718, 2020.

[4] S. Uddin, A. Khan, M. E. Hossain and M. A. Moni, "Comparing Different Supervised Machine Learning Algorithms for Disease Prediction," BMC Medical Informatics and Decision Making, vol. 19, pp. 1-16, 2019.

[5] M. Alweshah, W. A. AlZoubi and A. Alarabeyyat, "Cluster Based Data Reduction Method for Transaction Datasets," Proc. of IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE), pp. 78-83, Langkawi, Malaysia, 2015.

[6] K. Zukotynski, V. Gaudet, C. F. Uribe et al., "Machine Learning in Nuclear Medicine: Part 2?Neural Networks and Clinical Aspects," Journal of Nuclear Medicine, vol. 62, pp. 22-29, 2021.

[7] N. Wang, Y. Huang, H. Liu, Z. Zhang, L. Wei, X. Fei and H. Chen, "Study on the Semi-supervised Learning-based Patient Similarity from Heterogeneous Electronic Medical Records," BMC Medical Informatics and Decision Making, vol. 21, pp. 1-13, 2021.

[8] E. H. Houssein, I. E. Ibrahim, N. Neggaz, M. Hassaballah and Y. M. Wazery, "An Efficient ECG Arrhythmia Classification Method Based on Manta Ray Foraging Optimization," Expert Systems with Applications, vol. 181, p. 115131, 2021.

[9] E. H. Houssein, M. E. Hosney and D. Oliva, "A Hybrid Seagull Optimization Algorithm for Chemical Descriptors Classification," Proc. of the International Mobile, Intelligent and Ubiquitous Computing Conference (MIUCC), pp. 1-6, Cairo, Egypt, 2021.

[10] A. Almomani, M. Alweshah, S. Al Khalayleh, M. Al-Refai and R. Qashi, "Metaheuristic Algorithms- based Feature Selection Approach for Intrusion Detection," Chapter in Book: Machine Learning for Computer and Cyber Security, 1st Edn., CRC Press, pp. 184-208, 2019.

[11] H. Al Nsour, M. Alweshah, A. I. Hammouri, H. Al Ofeishat and S. Mirjalili, "A Hybrid Grey Wolf Optimiser Algorithm for Solving Time Series Classification Problems," Journal of Intelligent Systems, vol. 29, no. 1, pp. 846-857, 2018.

[12] M. Alweshah, L. Rababa, M. H. Ryalat, A. Al Momani and M. F. Ababneh, "African Buffalo Algorithm: Training the Probabilistic Neural Network to Solve Classification Problems," Journal of King Saud University-Computer and Information Sciences, DOI: 10.1016/j.jksuci.2020.07.004, 2020.

[13] O. Dorgham, M. Alweshah, M. Ryalat, J. Alshaer, M. Khader and S. Alkhalaileh, "Monarch Butterfly Optimization Algorithm for Computed Tomography Image Segmentation," Multimedia Tools and Applications, pp. 1-34, DOI: 10.1007/s11042-020-10147-6, 2021.

[14] M. Alweshah, "Solving Feature Selection Problems by Combining Mutation and Crossover Operations with the Monarch Butterfly Optimization Algorithm," Applied Intelligence, vol. 51, no. 1, pp. 1-24, 2020.

[15] M. Alweshah, H. Rashaideh, A. I. Hammouri, H. Tayyeb and M. Ababneh, "Solving Time Series Classification Problems Using Support Vector Machine and Neural Network," International Journal of Data Analysis Techniques and Strategies, vol. 9, pp. 237-247, 2017.

[16] B. Sathiyabhama et al., "A Novel Feature Selection Framework Based on Grey Wolf Optimizer for Mammogram Image Analysis," Neural Computing and Applications, vol. 33, pp. 14583?14602, 2021.

[17] M. Alweshah, E. Ramadan, M. H. Ryalat, M. Almi'ani and A. I. Hammouri, "Water Evaporation Algorithm with Probabilistic Neural Network for Solving Classification Problems," Jordanian Journal of Computers and Information Technology (JJCIT), vol. 6, no. 1, pp. 1-15, 2020.

[18] M. Alweshah, O. A. Alzubi, J. A. Alzubi and S. Alaqeel, "Solving Attribute Reduction Problem Using Wrapper Genetic Programming," International Journal of Computer Science and Network Security (IJCSNS), vol. 16, p. 77, 2016.

[19] M. Alweshah, S. Alkhalaileh, D. Albashish, M. Mafarja, Q. Bsoul and O. Dorgham, "A Hybrid Mine Blast Algorithm for Feature Selection Problems," Soft Computing, vol. 25, pp. 517-534, 2021.

[20] H. Sun, J. Jin, R. Xu and A. Cichocki, "Feature Selection Combining Filter and Wrapper Methods for Motor-Imagery Based Brain?Computer Interfaces," International Journal of Neural Systems, vol. 31, no. 9, p. 2150040, 2021.

[21] N. Darabi, A. Rezai and S. S. F. Hamidpour, "Breast Cancer Detection Using RSFS-based Feature Selection Algorithms in Thermal Images," Biomedical Engineering: Applications, Basis and Communications, vol. 33, no. 3, p. 2150020, 2021.

[22] M. Salimian, A. Rezai, S. Hamidpour and F. Khajeh-Khalili, "Effective Features in Thermal Images for Breast Cancer Detection," Proc. of the 2nd National Conf. on New Technologies in Electrical and Computer Engineering, Isfahan, Iran, pp. 1-7, 2019.

[23] M. Zarei, A. Rezai and S. S. Falahieh Hamidpour, "Breast Cancer Segmentation Based on Modified Gaussian Mean Shift Algorithm for Infrared Thermal Images," Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, vol. 9, no. 6, pp. 1-7, 2021.

[24] H. Y. Chong, H. J. Yap, S. C. Tan et al., "Advances of Metaheuristic Algorithms in Training Neural Networks for Industrial Applications," Soft Computing, vol. 25, pp. 11209-11233, 2021.

[25] Y. Xue, Y. Tang, X. Xu, J. Liang and F. Neri, "Multi-objective Feature Selection with Missing Data in Classification," IEEE Transactions on Emerging Topics in Computational Intelligence, DOI: 10.1109/TETCI.2021.3074147, pp. 1-10, 2021.

[26] F. A. Hashim, E. H. Houssein, K. Hussain, M. S. Mabrouk and W. Al-Atabany, "Honey Badger Algorithm: New Metaheuristic Algorithm for Solving Optimization Problems," Mathematics and Computers in Simulation, vol. 192, pp. 84-110, 2022.

[27] L. Abualigah, A. Diabat, S. Mirjalili, M. Abd Elaziz and A. H. Gandomi, "The Arithmetic Optimization Algorithm," Computer Methods in Applied Mechanics and Engineering, vol. 376, p. 113609, 2021.

[28] D. Simon, "Biogeography-based Optimization," IEEE Transactions on Evolutionary Computation, vol. 12, pp. 702-713, 2008.

[29] S. Khatir, S. Tiachacht, C. Le Thanh, E. Ghandourah, S. Mirjalili and M. A. Wahab, "An Improved Artificial Neural Network Using Arithmetic Optimization Algorithm for Damage Assessment in FGM Composite Plates," Composite Structures, vol. 273, p. 114287, 2021.

[30] L. Abualigah, A. Diabat, P. Sumari and A. H. Gandomi, "A Novel Evolutionary Arithmetic Optimization Algorithm for Multilevel Thresholding Segmentation of Covid-19 ct Images," Processes, vol. 9, p. 1155, 2021.

[31] M. Premkumar, P. Jangir, B. S. Kumar, R. Sowmya, H. H. Alhelou, L. Abualigah, A. R. Yildiz and S. Mirjalili, "A New Arithmetic Optimization Algorithm for Solving Real-world Multiobjective CEC- 2021 Constrained Optimization Problems: Diversity Analysis and Validations," IEEE Access, vol. 9, pp. 84263-84295, 2021.

[32] Y. Wu, "A Survey on Population-based Meta-heuristic Algorithms for Motion Planning of Aircraft," Swarm and Evolutionary Computation, vol. 62, p. 100844, 2021.

[33] D. Gürses, S. Bureerat, S. M. Sait and A. R. Yıldız, "Comparison of the Arithmetic Optimization Algorithm, the Slime Mold Optimization Algorithm, the Marine Predators Algorithm, the Salp Swarm Algorithm for Real-world Engineering Applications," Materials Testing, vol. 63, pp. 448-452, 2021.

[34] G. Dueck, "New Optimization Heuristics: The Great Deluge Algorithm and the Record-to-record Travel," Journal of Computational Physics, vol. 104, pp. 86-92, 1993.

[35] D. Landa-Silva and J. H. Obit, "Great Deluge with Non-linear Decay Rate for Solving Course Timetabling Problems," Proc. of the 4th International IEEE Conference on Intelligent Systems, pp. 8-11- 8-18, Varna, Bulgaria, 2008.

[36] S. Kifah and S. Abdullah, "An Adaptive Non-linear Great Deluge Algorithm for the Patient-admission Problem," Information Sciences, vol. 295, pp. 573-585, 2015.

[37] M. Mohmad Kahar and G. Kendall, "A Great Deluge Algorithm for a Real-world Examination Timetabling Problem," Journal of the Operational Research Society, vol. 66, pp. 116-133, 2015.

[38] S. Kassaymeh, S. Abdullah, M. A. Al-Betar and M. Alweshah, "Salp Swarm Optimizer for Modeling the Software Fault Prediction Problem," Journal of King Saud University-Computer and Information Sciences, In Press, DOI: 10.1016/j.jksuci.2021.01.015, 2021.

[39] M. Alweshah, S. Alkhalaileh, M. A. Al-Betar and A. A. Bakar, "Coronavirus Herd Immunity Optimizer with Greedy Crossover for Feature Selection in Medical Diagnosis," Knowledge-based Systems, vol. 235, p. 107629, DOI: 10.1016/j.knosys.2021.107629, 2021.

[40] R. Abu Khurmaa, I. Aljarah and A. Sharieh, "An Intelligent Feature Selection Approach Based on Moth Flame Optimization for Medical Diagnosis," Neural Computing and Applications, vol. 33, pp. 7165-7204, 2021.

[41] F. A. Hashim, K. Hussain, E. H. Houssein, M. S. Mabrouk and W. Al-Atabany, "Archimedes Optimization Algorithm: A New Metaheuristic Algorithm for Solving Optimization Problems," Applied Intelligence, vol. 51, pp. 1531-1551, 2021.