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Asad Mansoor Khan, Muhammad Usman Akram, Sajid Nazir, Taimur Hassan, Sajid Gul Khawaja, Tatheer Fatima. Multi-head deep learning framework for pulmonary disease detection and severity scoring with modified progressive learning. Biomed Signal Process Control 2023;85. [ DOI: 10.1016/j.bspc.2023.104855] [Reference Citation Analysis]
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Hou L, Li R, Mafarja M, Heidari AA, Liu L, Jin C, Zhou S, Chen H, Cai Z, Li C. Image segmentation of Intracerebral hemorrhage patients based on enhanced hunger Games search Optimizer. Biomedical Signal Processing and Control 2023;82:104511. [DOI: 10.1016/j.bspc.2022.104511] [Reference Citation Analysis]
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Zhao S, Wang P, Heidari AA, Zhao X, Chen H. Boosted crow search algorithm for handling multi-threshold image problems with application to X-ray images of COVID-19. Expert Syst Appl 2023;213:119095. [PMID: 36313263 DOI: 10.1016/j.eswa.2022.119095] [Reference Citation Analysis]
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Abualigah L, Habash M, Hanandeh ES, Hussein AM, Shinwan MA, Zitar RA, Jia H. Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation. J Bionic Eng 2023;:1-25. [PMID: 36777369 DOI: 10.1007/s42235-023-00332-2] [Reference Citation Analysis]
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Hao S, Huang C, Heidari AA, Xu Z, Chen H, Althobaiti MM, Mansour RF, Chen X. Performance optimization of water cycle algorithm for multilevel lupus nephritis image segmentation. Biomedical Signal Processing and Control 2023;80:104139. [DOI: 10.1016/j.bspc.2022.104139] [Reference Citation Analysis]
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Gharehchopogh FS, Ucan A, Ibrikci T, Arasteh B, Isik G. Slime Mould Algorithm: A Comprehensive Survey of Its Variants and Applications. Arch Comput Methods Eng 2023;:1-41. [PMID: 36685136 DOI: 10.1007/s11831-023-09883-3] [Reference Citation Analysis]
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Han Y, Chen W, Heidari AA, Chen H. Multi-verse Optimizer with Rosenbrock and Diffusion Mechanisms for Multilevel Threshold Image Segmentation from COVID-19 Chest X-Ray Images. J Bionic Eng 2023;:1-65. [PMID: 36619872 DOI: 10.1007/s42235-022-00295-w] [Reference Citation Analysis]
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Rather SA, Çiftçioğlu AÖ, Bala PS. Lévy flight and Chaos theory based metaheuristics for grayscale image thresholding. Comprehensive Metaheuristics 2023. [DOI: 10.1016/b978-0-323-91781-0.00012-0] [Reference Citation Analysis]
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Yan X, Zhang Y, Huang M, Yang X, Yan Y, Hu F. Graph-based medicine embedding learning via multiple attentions. Computers and Electrical Engineering 2023;105:108494. [DOI: 10.1016/j.compeleceng.2022.108494] [Reference Citation Analysis]
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Li J, Liu K, Hu Y, Zhang H, Heidari AA, Chen H, Zhang W, Algarni AD, Elmannai H. Eres-UNet++: Liver CT image segmentation based on high-efficiency channel attention and Res-UNet+. Comput Biol Med 2022;:106501. [PMID: 36635120 DOI: 10.1016/j.compbiomed.2022.106501] [Reference Citation Analysis]
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Chen H, Li C, Mafarja M, Heidari AA, Chen Y, Cai Z. Slime mould algorithm: a comprehensive review of recent variants and applications. International Journal of Systems Science 2022. [DOI: 10.1080/00207721.2022.2153635] [Reference Citation Analysis]
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Wei Zhu, Liu L, Kuang F, Li L, Xu S, Liang Y. An efficient multi-threshold image segmentation for skin cancer using boosting whale optimizer. Comput Biol Med 2022;151:106227. [PMID: 36368112 DOI: 10.1016/j.compbiomed.2022.106227] [Reference Citation Analysis]
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Chakraborty P, Nama S, Saha AK. A hybrid slime mould algorithm for global optimization. Multimed Tools Appl 2022. [DOI: 10.1007/s11042-022-14077-3] [Reference Citation Analysis]
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Wei Y, Othman Z, Daud KM, Yin S, Luo Q, Zhou Y. Equilibrium Optimizer and Slime Mould Algorithm with Variable Neighborhood Search for Job Shop Scheduling Problem. Mathematics 2022;10:4063. [DOI: 10.3390/math10214063] [Reference Citation Analysis]
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Zhang Y, Du S, Zhang Q. Improved Slime Mold Algorithm with Dynamic Quantum Rotation Gate and Opposition-Based Learning for Global Optimization and Engineering Design Problems. Algorithms 2022;15:317. [DOI: 10.3390/a15090317] [Reference Citation Analysis]
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Xu Z, Asghar Heidari A, Kuang F, Khalil A, Mafarja M, Zhang S, Chen H, Pan Z. Enhanced Gaussian Bare-Bones Grasshopper Optimization: Mitigating the Performance Concerns for Feature Selection. Expert Systems with Applications 2022. [DOI: 10.1016/j.eswa.2022.118642] [Reference Citation Analysis]
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Ren L, Zhao D, Zhao X, Chen W, Li L, Wu T, Liang G, Cai Z, Xu S. Multi-level thresholding segmentation for pathological images: Optimal performance design of a new modified differential evolution. Computers in Biology and Medicine 2022. [DOI: 10.1016/j.compbiomed.2022.105910] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
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Ma G, Yue X. An improved whale optimization algorithm based on multilevel threshold image segmentation using the Otsu method. Engineering Applications of Artificial Intelligence 2022;113:104960. [DOI: 10.1016/j.engappai.2022.104960] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
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Qi A, Zhao D, Yu F, Heidari AA, Wu Z, Cai Z, Alenezi F, Mansour RF, Chen H, Chen M. Directional mutation and crossover boosted ant colony optimization with application to COVID-19 X-ray image segmentation. Comput Biol Med 2022;148:105810. [PMID: 35868049 DOI: 10.1016/j.compbiomed.2022.105810] [Cited by in Crossref: 16] [Cited by in F6Publishing: 14] [Article Influence: 16.0] [Reference Citation Analysis]
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Miao H, Qiu Z, Zeng C. Multi-Strategy Improved Slime Mould Algorithm and its Application in Optimal Operation of Cascade Reservoirs. Water Resour Manage 2022;36:3029-48. [DOI: 10.1007/s11269-022-03183-4] [Reference Citation Analysis]
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Yin S, Luo Q, Zhou G, Zhou Y, Zhu B. An equilibrium optimizer slime mould algorithm for inverse kinematics of the 7-DOF robotic manipulator. Sci Rep 2022;12. [DOI: 10.1038/s41598-022-13516-3] [Reference Citation Analysis]
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Jin J, Fan J. Threshold Selection on Circular Histogram Using Renyi Entropy. Proceedings of the 4th International Symposium on Signal Processing Systems 2022. [DOI: 10.1145/3532342.3532351] [Reference Citation Analysis]
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Stoleru CA, Dulf EH, Ciobanu L. Automated detection of celiac disease using Machine Learning Algorithms. Sci Rep 2022;12:4071. [PMID: 35260574 DOI: 10.1038/s41598-022-07199-z] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
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Chen X, Huang H, Heidari AA, Sun C, Lv Y, Gui W, Liang G, Gu Z, Chen H, Li C, Chen P. An efficient multilevel thresholding image segmentation method based on the slime mould algorithm with bee foraging mechanism: A real case with lupus nephritis images. Computers in Biology and Medicine 2022;142:105179. [DOI: 10.1016/j.compbiomed.2021.105179] [Cited by in Crossref: 12] [Cited by in F6Publishing: 12] [Article Influence: 12.0] [Reference Citation Analysis]
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Ren L, Heidari AA, Cai Z, Shao Q, Liang G, Chen H, Pan Z. Gaussian kernel probability-driven slime mould algorithm with new movement mechanism for multi-level image segmentation. Measurement 2022;192:110884. [DOI: 10.1016/j.measurement.2022.110884] [Cited by in Crossref: 3] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]
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Aranguren I, Valdivia A, Pérez-cisneros M, Oliva D, Osuna-enciso V. Digital image thresholding by using a lateral inhibition 2D histogram and a Mutated Electromagnetic Field Optimization. Multimed Tools Appl 2022;81:10023-49. [DOI: 10.1007/s11042-022-11959-4] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
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Hu J, Gui W, Heidari AA, Cai Z, Liang G, Chen H, Pan Z. Dispersed foraging slime mould algorithm: Continuous and binary variants for global optimization and wrapper-based feature selection. Knowledge-Based Systems 2022;237:107761. [DOI: 10.1016/j.knosys.2021.107761] [Cited by in Crossref: 34] [Cited by in F6Publishing: 25] [Article Influence: 34.0] [Reference Citation Analysis]
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Chakraborty S, Sharma S, Saha AK, Saha A. A novel improved whale optimization algorithm to solve numerical optimization and real-world applications. Artif Intell Rev. [DOI: 10.1007/s10462-021-10114-z] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
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Gao H, Liang G, Chen H. Multi-Population Enhanced Slime Mould Algorithm and with Application to Postgraduate Employment Stability Prediction. Electronics 2022;11:209. [DOI: 10.3390/electronics11020209] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
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Yin S, Luo Q, Zhou Y. EOSMA: An Equilibrium Optimizer Slime Mould Algorithm for Engineering Design Problems. Arab J Sci Eng. [DOI: 10.1007/s13369-021-06513-7] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
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Su H, Zhao D, Yu F, Heidari AA, Zhang Y, Chen H, Li C, Pan J, Quan S. Horizontal and vertical search artificial bee colony for image segmentation of COVID-19 X-ray images. Comput Biol Med 2022;142:105181. [PMID: 35016099 DOI: 10.1016/j.compbiomed.2021.105181] [Cited by in Crossref: 28] [Cited by in F6Publishing: 25] [Article Influence: 28.0] [Reference Citation Analysis]
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Chen C, Wang X, Heidari AA, Yu H, Chen H. Multi-Threshold Image Segmentation of Maize Diseases Based on Elite Comprehensive Particle Swarm Optimization and Otsu. Front Plant Sci 2021;12:789911. [PMID: 34966405 DOI: 10.3389/fpls.2021.789911] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
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Lin S, Jia H, Abualigah L, Altalhi M. Enhanced Slime Mould Algorithm for Multilevel Thresholding Image Segmentation Using Entropy Measures. Entropy (Basel) 2021;23:1700. [PMID: 34946006 DOI: 10.3390/e23121700] [Cited by in Crossref: 14] [Cited by in F6Publishing: 14] [Article Influence: 7.0] [Reference Citation Analysis]
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Tang AD, Tang SQ, Han T, Zhou H, Xie L. A Modified Slime Mould Algorithm for Global Optimization. Comput Intell Neurosci 2021;2021:2298215. [PMID: 34912443 DOI: 10.1155/2021/2298215] [Cited by in Crossref: 4] [Cited by in F6Publishing: 7] [Article Influence: 2.0] [Reference Citation Analysis]
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Liu Q, Qi Q, Jia H, Li N. An Improved Slime Mould Algorithm with Quasi Reflection-based Learning for Global Optimization Problems. 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys) 2021. [DOI: 10.1109/hpcc-dss-smartcity-dependsys53884.2021.00298] [Reference Citation Analysis]
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Zhang Q, Wang Z, Heidari AA, Gui W, Shao Q, Chen H, Zaguia A, Turabieh H, Chen M. Gaussian Barebone Salp Swarm Algorithm with Stochastic Fractal Search for medical image segmentation: A COVID-19 case study. Comput Biol Med 2021;139:104941. [PMID: 34801864 DOI: 10.1016/j.compbiomed.2021.104941] [Cited by in Crossref: 19] [Cited by in F6Publishing: 20] [Article Influence: 9.5] [Reference Citation Analysis]
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Zhao S, Wang P, Heidari AA, Chen H, He W, Xu S. Performance optimization of salp swarm algorithm for multi-threshold image segmentation: Comprehensive study of breast cancer microscopy. Comput Biol Med 2021;139:105015. [PMID: 34800808 DOI: 10.1016/j.compbiomed.2021.105015] [Cited by in Crossref: 14] [Cited by in F6Publishing: 20] [Article Influence: 7.0] [Reference Citation Analysis]
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Pare S, Mittal H, Sajid M, Bansal JC, Saxena A, Jan T, Pedrycz W, Prasad M. Remote Sensing Imagery Segmentation: A Hybrid Approach. Remote Sensing 2021;13:4604. [DOI: 10.3390/rs13224604] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
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Weng X, Heidari AA, Liang G, Chen H, Ma X. An evolutionary Nelder–Mead slime mould algorithm with random learning for efficient design of photovoltaic models. Energy Reports 2021;7:8784-804. [DOI: 10.1016/j.egyr.2021.11.019] [Cited by in Crossref: 7] [Cited by in F6Publishing: 9] [Article Influence: 3.5] [Reference Citation Analysis]
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Liu Y, Heidari AA, Ye X, Liang G, Chen H, He C. Boosting slime mould algorithm for parameter identification of photovoltaic models. Energy 2021;234:121164. [DOI: 10.1016/j.energy.2021.121164] [Cited by in Crossref: 29] [Cited by in F6Publishing: 32] [Article Influence: 14.5] [Reference Citation Analysis]
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Ahmadianfar I, Gong W, Heidari AA, Golilarz NA, Samadi-koucheksaraee A, Chen H. Gradient-based optimization with ranking mechanisms for parameter identification of photovoltaic systems. Energy Reports 2021;7:3979-97. [DOI: 10.1016/j.egyr.2021.06.064] [Cited by in Crossref: 22] [Cited by in F6Publishing: 24] [Article Influence: 11.0] [Reference Citation Analysis]
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Zhao F, Liu F, Li C, Liu H, Lan R, Fan J. Coarse–fine surrogate model driven multiobjective evolutionary fuzzy clustering algorithm with dual memberships for noisy image segmentation. Applied Soft Computing 2021;112:107778. [DOI: 10.1016/j.asoc.2021.107778] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
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Liu L, Zhao D, Yu F, Heidari AA, Ru J, Chen H, Mafarja M, Turabieh H, Pan Z. Performance optimization of differential evolution with slime mould algorithm for multilevel breast cancer image segmentation. Comput Biol Med 2021;138:104910. [PMID: 34638022 DOI: 10.1016/j.compbiomed.2021.104910] [Cited by in Crossref: 23] [Cited by in F6Publishing: 30] [Article Influence: 11.5] [Reference Citation Analysis]
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Wang S, Liu Q, Liu Y, Jia H, Abualigah L, Zheng R, Wu D. A Hybrid SSA and SMA with Mutation Opposition-Based Learning for Constrained Engineering Problems. Comput Intell Neurosci 2021;2021:6379469. [PMID: 34531910 DOI: 10.1155/2021/6379469] [Cited by in Crossref: 22] [Cited by in F6Publishing: 23] [Article Influence: 11.0] [Reference Citation Analysis]
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Shakeel CS, Khan SJ, Chaudhry B, Aijaz SF, Hassan U. Classification Framework for Healthy Hairs and Alopecia Areata: A Machine Learning (ML) Approach. Comput Math Methods Med 2021;2021:1102083. [PMID: 34434248 DOI: 10.1155/2021/1102083] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 0.5] [Reference Citation Analysis]
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Shi B, Ye H, Zheng J, Zhu Y, Heidari AA, Zheng L, Chen H, Wang L, Wu P. Early Recognition and Discrimination of COVID-19 Severity Using Slime Mould Support Vector Machine for Medical Decision-Making. IEEE Access 2021;9:121996-2015. [DOI: 10.1109/access.2021.3108447] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
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