{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T03:17:47Z","timestamp":1784085467711,"version":"3.55.0"},"reference-count":59,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,27]],"date-time":"2025-12-27T00:00:00Z","timestamp":1766793600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,12,27]],"date-time":"2025-12-27T00:00:00Z","timestamp":1766793600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Evolving Systems"],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1007\/s12530-025-09785-8","type":"journal-article","created":{"date-parts":[[2025,12,27]],"date-time":"2025-12-27T09:32:09Z","timestamp":1766827929000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Colon disorder classification using altruistic genetic algorithm based fused deep feature selection method"],"prefix":"10.1007","volume":"17","author":[{"given":"Anurup","family":"Naskar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shivam","family":"Singh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ram","family":"Sarkar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,12,27]]},"reference":[{"key":"9785_CR1","first-page":"476","volume":"19","author":"S Aalaei","year":"2016","unstructured":"Aalaei S, Shahraki H, Rowhanimanesh A, Eslami S (2016) Feature selection using genetic algorithm for breast cancer diagnosis: experiment on three different datasets. Iran J Basic Med Sci 19:476\u2013482","journal-title":"Iran J Basic Med Sci"},{"key":"9785_CR2","doi-asserted-by":"publisher","first-page":"1902","DOI":"10.7717\/peerj-cs.1902","volume":"10","author":"S Al-Otaibi","year":"2024","unstructured":"Al-Otaibi S, Rehman A, Mujahid M, Alotaibi S, Saba T (2024) Efficient-gastro: optimized efficientnet model for the detection of gastrointestinal disorders using transfer learning and wireless capsule endoscopy images. PeerJ Comput Sci 10:1902","journal-title":"PeerJ Comput Sci"},{"issue":"3","key":"9785_CR3","doi-asserted-by":"publisher","first-page":"12759","DOI":"10.1111\/exsy.12759","volume":"39","author":"ZAA Alyasseri","year":"2022","unstructured":"Alyasseri ZAA, Al-Betar MA, Doush IA, Awadallah MA, Abasi AK, Makhadmeh SN, Alomari OA, Abdulkareem KH, Adam A, Damasevicius R et al (2022) Review on covid-19 diagnosis models based on machine learning and deep learning approaches. Exp Syst 39(3):12759","journal-title":"Exp Syst"},{"key":"9785_CR4","doi-asserted-by":"publisher","first-page":"195929","DOI":"10.1109\/ACCESS.2020.3031718","volume":"8","author":"T Bhattacharyya","year":"2020","unstructured":"Bhattacharyya T, Chatterjee B, Singh PK, Yoon JH, Geem ZW, Sarkar R (2020) Mayfly in harmony: a new hybrid meta-heuristic feature selection algorithm. IEEE Access 8:195929\u2013195945","journal-title":"IEEE Access"},{"issue":"1","key":"9785_CR5","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.ejor.2016.07.012","volume":"258","author":"EK Burke","year":"2017","unstructured":"Burke EK, Bykov Y (2017) The late acceptance hill-climbing heuristic. Eur J Oper Res 258(1):70\u201378","journal-title":"Eur J Oper Res"},{"key":"9785_CR6","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-024-18391-w","author":"S Charfi","year":"2024","unstructured":"Charfi S, El Ansari M, Koutti L, Ellahyani A, Eljaafari I (2024) Abnormalities detection from wireless capsule endoscopy images based on embedding learning with triplet loss. Multimedia Tools Appl. https:\/\/doi.org\/10.1007\/s11042-024-18391-w","journal-title":"Multimedia Tools Appl"},{"key":"9785_CR7","doi-asserted-by":"crossref","unstructured":"Chen C-FR, Fan Q, Panda R (2021) Crossvit: cross-attention multi-scale vision transformer for image classification. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 357\u2013366","DOI":"10.1109\/ICCV48922.2021.00041"},{"key":"9785_CR8","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1007\/s11390-021-0849-3","volume":"36","author":"H Chen","year":"2021","unstructured":"Chen H, Liu J, Wen Q-M, Zuo Z-Q, Liu J-S, Feng J, Pang B-C, Xiao D (2021) Cytobrain: cervical cancer screening system based on deep learning technology. J Comput Sci Technol 36:347\u2013360","journal-title":"J Comput Sci Technol"},{"issue":"3","key":"9785_CR9","doi-asserted-by":"publisher","first-page":"915","DOI":"10.1007\/s13246-020-00888-x","volume":"43","author":"D Das","year":"2020","unstructured":"Das D, Santosh KC, Pal U (2020) Truncated inception net: Covid-19 outbreak screening using chest x-rays. Phys Eng Sci Med 43(3):915\u2013925. https:\/\/doi.org\/10.1007\/s13246-020-00888-x","journal-title":"Phys Eng Sci Med"},{"key":"9785_CR10","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1007\/s11277-016-3536-x","volume":"93","author":"SP Deenan","year":"2017","unstructured":"Deenan SP, SatheeshKumar J (2017) An efficient image contrast enhancement algorithm using genetic algorithm and fuzzy intensification operator. Wirel Pers Commun 93:223\u2013244. https:\/\/doi.org\/10.1007\/s11277-016-3536-x","journal-title":"Wirel Pers Commun"},{"key":"9785_CR11","doi-asserted-by":"crossref","unstructured":"Dwivedi AK, Srivastava G, Pradhan N (2023) Nff: a novel nested feature fusion method for efficient and early detection of colorectal carcinoma. In: Reddy KA, Devi BR, George B, Raju KS, Sellathurai M (eds) Proceedings of fourth international conference on computer and communication technologies, pp 297\u2013309. Springer, Singapore","DOI":"10.1007\/978-981-19-8563-8_28"},{"issue":"16","key":"9785_CR12","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/aad51c","volume":"63","author":"S Fan","year":"2018","unstructured":"Fan S, Xu L, Fan Y, Wei K, Li L (2018) Computer-aided detection of small intestinal ulcer and erosion in wireless capsule endoscopy images. Phys Med Biol 63(16):165001","journal-title":"Phys Med Biol"},{"key":"9785_CR13","doi-asserted-by":"crossref","unstructured":"Ghahramani M, Shiri N (2024) An adaptive neuro-fuzzy inference system optimized by genetic algorithm for brain tumour detection in magnetic resonance images. IET Image Process","DOI":"10.1049\/ipr2.13031"},{"key":"9785_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s12065-019-00218-5","volume":"14","author":"R Guha","year":"2021","unstructured":"Guha R, Ghosh M, Kapri S, Shaw S, Mutsuddi S, Bhateja V, Sarkar R (2021) Deluge based genetic algorithm for feature selection. Evol Intell 14:1\u201311. https:\/\/doi.org\/10.1007\/s12065-019-00218-5","journal-title":"Evol Intell"},{"key":"9785_CR15","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Identity mappings in deep residual networks. In: Computer vision\u2013ECCV 2016: 14th European conference, Amsterdam, The Netherlands, October 11\u201314, 2016, proceedings, part IV 14, pp 630\u2013645. Springer, Berlin","DOI":"10.1007\/978-3-319-46493-0_38"},{"key":"9785_CR16","doi-asserted-by":"crossref","unstructured":"Holland JH (1992) Genetic algorithms. Sci Am 267(1):66\u201373. Accessed 27 July 2023","DOI":"10.1038\/scientificamerican0792-66"},{"key":"9785_CR17","doi-asserted-by":"publisher","unstructured":"Hosain AKMS, Islam M, Mehedi MHK, Kabir IE, Khan ZT (2022) Gastrointestinal disorder detection with a transformer based approach. In: 2022 IEEE 13th annual information technology, electronics and mobile communication conference (IEMCON), pp 0280\u20130285. https:\/\/doi.org\/10.1109\/IEMCON56893.2022.9946531","DOI":"10.1109\/IEMCON56893.2022.9946531"},{"issue":"27","key":"9785_CR18","doi-asserted-by":"publisher","first-page":"38429","DOI":"10.1007\/s11042-022-13158-7","volume":"81","author":"S Hossain","year":"2022","unstructured":"Hossain S, Mukhopadhyay S, Ray B, Ghosal SK, Sarkar R (2022) A secured image steganography method based on ballot transform and genetic algorithm. Multimedia Tools Appl 81(27):38429\u201338458","journal-title":"Multimedia Tools Appl"},{"key":"9785_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.104094","volume":"127","author":"S Jain","year":"2020","unstructured":"Jain S, Seal A, Ojha A, Krejcar O, Bure\u0161 J, Tachec\u00ed I, Yazidi A (2020) Detection of abnormality in wireless capsule endoscopy images using fractal features. Comput Biol Med 127:104094","journal-title":"Comput Biol Med"},{"key":"9785_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104789","volume":"137","author":"S Jain","year":"2021","unstructured":"Jain S, Seal A, Ojha A, Yazidi A, Bures J, Tacheci I, Krejcar O (2021) A deep CNN model for anomaly detection and localization in wireless capsule endoscopy images. Comput Biol Med 137:104789","journal-title":"Comput Biol Med"},{"issue":"4","key":"9785_CR21","doi-asserted-by":"publisher","first-page":"475","DOI":"10.1007\/s40846-023-00815-x","volume":"43","author":"S Jain","year":"2023","unstructured":"Jain S, Seal A, Ojha A (2023) A convolutional neural network with meta-feature learning for wireless capsule endoscopy image classification. J Med Bio Eng 43(4):475\u2013494","journal-title":"J Med Bio Eng"},{"key":"9785_CR22","doi-asserted-by":"crossref","unstructured":"Jain S, Seal A, Ojha A (2021) Localization of polyps in WCE images using deep learning segmentation methods: a comparative study. In: International conference on computer vision and image processing, pp 538\u2013549. Springer, Berlin","DOI":"10.1007\/978-3-031-11346-8_46"},{"issue":"1","key":"9785_CR23","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1186\/s40537-019-0192-5","volume":"6","author":"JM Johnson","year":"2019","unstructured":"Johnson JM, Khoshgoftaar TM (2019) Survey on deep learning with class imbalance. J Big Data 6(1):27. https:\/\/doi.org\/10.1186\/s40537-019-0192-5","journal-title":"J Big Data"},{"issue":"17","key":"9785_CR24","doi-asserted-by":"publisher","first-page":"2914","DOI":"10.1016\/j.neucom.2011.03.034","volume":"74","author":"MM Kabir","year":"2011","unstructured":"Kabir MM, Shahjahan M, Murase K (2011) A new local search based hybrid genetic algorithm for feature selection. Neurocomputing 74(17):2914\u20132928. https:\/\/doi.org\/10.1016\/j.neucom.2011.03.034","journal-title":"Neurocomputing"},{"key":"9785_CR25","doi-asserted-by":"publisher","first-page":"132850","DOI":"10.1109\/ACCESS.2020.3010448","volume":"8","author":"MA Khan","year":"2020","unstructured":"Khan MA, Kadry S, Alhaisoni M, Nam Y, Zhang Y, Rajinikanth V, Sarfraz MS (2020) Computer-aided gastrointestinal diseases analysis from wireless capsule endoscopy: a framework of best features selection. IEEE Access 8:132850\u2013132859. https:\/\/doi.org\/10.1109\/ACCESS.2020.3010448","journal-title":"IEEE Access"},{"key":"9785_CR26","doi-asserted-by":"publisher","first-page":"2435","DOI":"10.1007\/s11277-018-5923-y","volume":"103","author":"S Kumar","year":"2018","unstructured":"Kumar S, Singh S, Kumar J (2018) Automatic live facial expression detection using genetic algorithm with haar wavelet features and SVM. Wireless Pers Commun 103:2435\u20132453","journal-title":"Wireless Pers Commun"},{"issue":"15","key":"9785_CR27","doi-asserted-by":"publisher","first-page":"6611","DOI":"10.1016\/j.eswa.2014.04.033","volume":"41","author":"C-H Lin","year":"2014","unstructured":"Lin C-H, Chen H-Y, Wu Y-S (2014) Study of image retrieval and classification based on adaptive features using genetic algorithm feature selection. Exp Syst Appl 41(15):6611\u20136621. https:\/\/doi.org\/10.1016\/j.eswa.2014.04.033","journal-title":"Exp Syst Appl"},{"issue":"5","key":"9785_CR28","doi-asserted-by":"publisher","first-page":"562","DOI":"10.1002\/jemt.23447","volume":"83","author":"A Majid","year":"2020","unstructured":"Majid A, Khan MA, Yasmin M, Rehman A, Yousafzai A, Tariq U (2020) Classification of stomach infections: a paradigm of convolutional neural network along with classical features fusion and selection. Microsc Res Tech 83(5):562\u2013576. https:\/\/doi.org\/10.1002\/jemt.23447","journal-title":"Microsc Res Tech"},{"key":"9785_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.106854","volume":"158","author":"S Marjit","year":"2023","unstructured":"Marjit S, Bhattacharyya T, Chatterjee B, Sarkar R (2023) Simulated annealing aided genetic algorithm for gene selection from microarray data. Comput Biol Med 158:106854. https:\/\/doi.org\/10.1016\/j.compbiomed.2023.106854","journal-title":"Comput Biol Med"},{"key":"9785_CR30","doi-asserted-by":"crossref","unstructured":"Meng L, Li H, Chen B-C, Lan S, Wu Z, Jiang Y-G, Lim S-N (2022) Adavit: adaptive vision transformers for efficient image recognition. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 12309\u201312318","DOI":"10.1109\/CVPR52688.2022.01199"},{"key":"9785_CR31","doi-asserted-by":"publisher","unstructured":"Montalbo FJ, Hernandez A (2020) An optimized classification model for Coffea Liberica disease using deep convolutional neural networks, pp 213\u2013218. https:\/\/doi.org\/10.1109\/CSPA48992.2020.9068683","DOI":"10.1109\/CSPA48992.2020.9068683"},{"key":"9785_CR32","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2022.103683","volume":"76","author":"FJP Montalbo","year":"2022","unstructured":"Montalbo FJP (2022) Diagnosing gastrointestinal diseases from endoscopy images through a multi-fused CNN with auxiliary layers, alpha dropouts, and a fusion residual block. Biomed Signal Process Control 76:103683. https:\/\/doi.org\/10.1016\/j.bspc.2022.103683","journal-title":"Biomed Signal Process Control"},{"key":"9785_CR33","doi-asserted-by":"publisher","unstructured":"Oliveira LS, Sabourin R, Bortolozzi F, Suen CY (2002) Feature selection using multi-objective genetic algorithms for handwritten digit recognition. In: 2002 international conference on pattern recognition, 1:568\u20135711. https:\/\/doi.org\/10.1109\/ICPR.2002.1044794","DOI":"10.1109\/ICPR.2002.1044794"},{"issue":"4, Part 2","key":"9785_CR34","doi-asserted-by":"publisher","first-page":"2052","DOI":"10.1016\/j.eswa.2013.09.004","volume":"41","author":"S Oreski","year":"2014","unstructured":"Oreski S, Oreski G (2014) Genetic algorithm-based heuristic for feature selection in credit risk assessment. Exp Syst Appl 41(4, Part 2):2052\u20132064. https:\/\/doi.org\/10.1016\/j.eswa.2013.09.004","journal-title":"Exp Syst Appl"},{"key":"9785_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.105610","volume":"146","author":"G Pahuja","year":"2022","unstructured":"Pahuja G, Prasad B (2022) Deep learning architectures for Parkinson\u2019s disease detection by using multi-modal features. Comput Biol Med 146:105610","journal-title":"Comput Biol Med"},{"key":"9785_CR36","doi-asserted-by":"publisher","unstructured":"Pogorelov K, Randel KR, Griwodz C, Eskeland SL, Lange T, Johansen D, Spampinato C, Dang-Nguyen D-T, Lux M, Schmidt PT, Riegler M, Halvorsen P (2017) Kvasir: a multi-class image dataset for computer aided gastrointestinal disease detection. In: Proceedings of the 8th ACM on multimedia systems conference. MMSys\u201917, pp 164\u2013169. Association for computing machinery, New York, NY, USA. https:\/\/doi.org\/10.1145\/3083187.3083212","DOI":"10.1145\/3083187.3083212"},{"key":"9785_CR37","doi-asserted-by":"publisher","first-page":"99227","DOI":"10.1109\/ACCESS.2020.2996770","volume":"8","author":"S Poudel","year":"2020","unstructured":"Poudel S, Kim YJ, Vo DM, Lee S-W (2020) Colorectal disease classification using efficiently scaled dilation in convolutional neural network. IEEE Access 8:99227\u201399238. https:\/\/doi.org\/10.1109\/ACCESS.2020.2996770","journal-title":"IEEE Access"},{"key":"9785_CR38","doi-asserted-by":"crossref","unstructured":"Prasetio RT (2020) Genetic algorithm to optimize k-nearest neighbor parameter for benchmarked medical datasets classification. J Online Inform, 153\u2013160","DOI":"10.15575\/join.v5i2.656"},{"issue":"1","key":"9785_CR39","first-page":"1","volume":"25","author":"K Pretorius","year":"2024","unstructured":"Pretorius K, Pillay N (2024) Neural network crossover in genetic algorithms using genetic programming. Genet Progr Evol Mach 25(1):1\u201330","journal-title":"Genet Progr Evol Mach"},{"key":"9785_CR40","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1016\/j.neucom.2021.12.090","volume":"478","author":"J Qin","year":"2022","unstructured":"Qin J, Liu F, Liu K, Jeon G, Yang X (2022) Lightweight hierarchical residual feature fusion network for single-image super-resolution. Neurocomputing 478:104\u2013123. https:\/\/doi.org\/10.1016\/j.neucom.2021.12.090","journal-title":"Neurocomputing"},{"key":"9785_CR41","first-page":"272","volume":"4","author":"G Ravi Kumar","year":"2014","unstructured":"Ravi Kumar G, Ramachandra G, Nagamani K (2014) An efficient feature selection system to integrating SVM with genetic algorithm for large medical datasets. Int J Adv Res Comput Sci Soft Eng 4:272\u2013277","journal-title":"Int J Adv Res Comput Sci Soft Eng"},{"issue":"20","key":"9785_CR42","doi-asserted-by":"publisher","first-page":"4209","DOI":"10.3390\/app9204209","volume":"9","author":"Y Ren","year":"2019","unstructured":"Ren Y, Yang J, Zhang Q, Guo Z (2019) Multi-feature fusion with convolutional neural network for ship classification in optical images. Appl Sci 9(20):4209. https:\/\/doi.org\/10.3390\/app9204209","journal-title":"Appl Sci"},{"key":"9785_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.107682","volume":"130","author":"S Sakthipriya","year":"2024","unstructured":"Sakthipriya S, Naresh R (2024) Precision agriculture based on convolutional neural network in rice production nutrient management using machine learning genetic algorithm. Eng Appl Artif Intell 130:107682","journal-title":"Eng Appl Artif Intell"},{"key":"9785_CR44","doi-asserted-by":"crossref","unstructured":"Sandler M, Howard A, Zhu M, Zhmoginov A, Chen L-C (2019) MobileNetV2: inverted residuals and linear bottlenecks","DOI":"10.1109\/CVPR.2018.00474"},{"key":"9785_CR45","doi-asserted-by":"publisher","DOI":"10.1007\/s40799-021-00470-4","author":"S Sarkar","year":"2021","unstructured":"Sarkar S, Mali K, Sarkar R (2021) A genetic algorithm based feature selection approach for microstructural image classification. Exp Tech. https:\/\/doi.org\/10.1007\/s40799-021-00470-4","journal-title":"Exp Tech"},{"issue":"2","key":"9785_CR46","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1007\/s11548-013-0926-3","volume":"9","author":"J Silva","year":"2014","unstructured":"Silva J, Histace A, Romain O, Dray X, Granado B (2014) Toward embedded detection of polyps in WCE images for early diagnosis of colorectal cancer. Int J Comput Assist Radiol Surg 9(2):283\u2013293. https:\/\/doi.org\/10.1007\/s11548-013-0926-3","journal-title":"Int J Comput Assist Radiol Surg"},{"key":"9785_CR47","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0117988","author":"O Soufan","year":"2015","unstructured":"Soufan O, Kleftogiannis D, Kalnis P, Bajic V (2015) Dwfs: a wrapper feature selection tool based on a parallel genetic algorithm. PLoS ONE. https:\/\/doi.org\/10.1371\/journal.pone.0117988","journal-title":"PLoS ONE"},{"issue":"1","key":"9785_CR48","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava N, Hinton G, Krizhevsky A, Sutskever I, Salakhutdinov R (2014) Dropout: a simple way to prevent neural networks from overfitting. J Mach Learn Res 15(1):1929\u20131958","journal-title":"J Mach Learn Res"},{"key":"9785_CR49","doi-asserted-by":"crossref","unstructured":"Suman S, Hussin FA, Malik A, Ho S-H, Hilmi I, Leow A, Goh K-L (2017) Feature selection and classification of ulcerated lesions using statistical analysis for WCE images","DOI":"10.3390\/app7101097"},{"key":"9785_CR50","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.compmedimag.2019.05.001","volume":"75","author":"ZNK Swati","year":"2019","unstructured":"Swati ZNK, Zhao Q, Kabir M, Ali F, Ali Z, Ahmed S, Lu J (2019) Brain tumor classification for MR images using transfer learning and fine-tuning. Comput Med Imag Graph 75:34\u201346. https:\/\/doi.org\/10.1016\/j.compmedimag.2019.05.001","journal-title":"Comput Med Imag Graph"},{"key":"9785_CR51","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-020-03378-9","author":"J Too","year":"2021","unstructured":"Too J, Abdullah AR (2021) A new and fast rival genetic algorithm for feature selection. J Supercomput. https:\/\/doi.org\/10.1007\/s11227-020-03378-9","journal-title":"J Supercomput"},{"issue":"10","key":"9785_CR52","doi-asserted-by":"publisher","first-page":"7498","DOI":"10.3390\/curroncol29100590","volume":"29","author":"S Tummala","year":"2022","unstructured":"Tummala S, Kadry S, Bukhari SAC, Rauf HT (2022) Classification of brain tumor from magnetic resonance imaging using vision transformers ensembling. Curr Oncol 29(10):7498\u20137511","journal-title":"Curr Oncol"},{"key":"9785_CR53","doi-asserted-by":"publisher","unstructured":"Vaishali R, Sasikala R, Ramasubbareddy S, Remya S, Nalluri S (2017) Genetic algorithm based feature selection and moe fuzzy classification algorithm on pima Indians diabetes dataset. In: 2017 International conference on computing networking and informatics (ICCNI), pp 1\u20135. https:\/\/doi.org\/10.1109\/ICCNI.2017.8123815","DOI":"10.1109\/ICCNI.2017.8123815"},{"key":"9785_CR54","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2014\/526801","volume":"2014","author":"K Varpa","year":"2014","unstructured":"Varpa K, Iltanen K, Juhola M (2014) Genetic algorithm based approach in attribute weighting for a medical data set. J Comput Med 2014:1\u201311. https:\/\/doi.org\/10.1155\/2014\/526801","journal-title":"J Comput Med"},{"key":"9785_CR55","doi-asserted-by":"publisher","first-page":"687456","DOI":"10.3389\/fnagi.2021.687456","volume":"13","author":"S-H Wang","year":"2021","unstructured":"Wang S-H, Zhou Q, Yang M, Zhang Y-D (2021) Advian: Alzheimer\u2019s disease VGG-inspired attention network based on convolutional block attention module and multiple way data augmentation. Front Aging Neurosci 13:687456. https:\/\/doi.org\/10.3389\/fnagi.2021.687456","journal-title":"Front Aging Neurosci"},{"key":"9785_CR56","doi-asserted-by":"crossref","unstructured":"Woo S, Park J, Lee J-Y, Kweon IS (2018) CBAM: convolutional block attention module","DOI":"10.1007\/978-3-030-01234-2_1"},{"issue":"1","key":"9785_CR57","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1007\/s10489-023-05207-x","volume":"54","author":"Y Xue","year":"2024","unstructured":"Xue Y, Yao W, Peng S, Yao S (2024) Automatic filter pruning algorithm for image classification. Appl Intell 54(1):216\u2013230","journal-title":"Appl Intell"},{"key":"9785_CR58","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TIM.2024.3374285","volume":"73","author":"B Ye","year":"2024","unstructured":"Ye B, Shu Z, Wang B, Wang S, Fu Y, Zhang L, Qi B, Dwivedi AK, Liu S (2024) Attention mechanism guided se + resnet-h model for gastrointestinal endoscopy image classification. IEEE Trans Instrum Meas 73:1\u201313. https:\/\/doi.org\/10.1109\/TIM.2024.3374285","journal-title":"IEEE Trans Instrum Meas"},{"issue":"1","key":"9785_CR59","doi-asserted-by":"publisher","first-page":"3041117","DOI":"10.1155\/2022\/3041117","volume":"2022","author":"Y Zheng","year":"2022","unstructured":"Zheng Y, Jiang W (2022) Evaluation of vision transformers for traffic sign classification. Wirel Commun Mob Comput 2022(1):3041117","journal-title":"Wirel Commun Mob Comput"}],"container-title":["Evolving Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12530-025-09785-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12530-025-09785-8","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12530-025-09785-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T05:17:53Z","timestamp":1773119873000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12530-025-09785-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,27]]},"references-count":59,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["9785"],"URL":"https:\/\/doi.org\/10.1007\/s12530-025-09785-8","relation":{},"ISSN":["1868-6478","1868-6486"],"issn-type":[{"value":"1868-6478","type":"print"},{"value":"1868-6486","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,27]]},"assertion":[{"value":"6 April 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. No funding was received to assist with the preparation of this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interest"}}],"article-number":"18"}}