{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T16:25:20Z","timestamp":1767889520219,"version":"3.49.0"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T00:00:00Z","timestamp":1767830400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T00:00:00Z","timestamp":1767830400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100007831","name":"University of Tabriz","doi-asserted-by":"publisher","award":["S\/1767"],"award-info":[{"award-number":["S\/1767"]}],"id":[{"id":"10.13039\/501100007831","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Netw Model Anal Health Inform Bioinforma"],"DOI":"10.1007\/s13721-025-00715-x","type":"journal-article","created":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T11:58:15Z","timestamp":1767873495000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Introducing high performance hybrid multi classification approach for medical data: TWV-KNN algorithm"],"prefix":"10.1007","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-8296-1816","authenticated-orcid":false,"given":"Shahrzad","family":"Pouramirarsalani","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7490-4422","authenticated-orcid":false,"given":"Somayeh","family":"Makouei","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7448-0292","authenticated-orcid":false,"given":"Karim","family":"Abbasian","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,8]]},"reference":[{"key":"715_CR1","doi-asserted-by":"publisher","DOI":"10.1201\/9781003159834","volume-title":"Foundations of statistics for data scientists: With R and Python","author":"A Agresti","year":"2021","unstructured":"Agresti A, Kateri M (2021) Foundations of statistics for data scientists: With R and Python. Chapman and Hall\/CRC"},{"issue":"12","key":"715_CR2","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics14121265","volume":"14","author":"MA Al-Antari","year":"2024","unstructured":"Al-Antari MA (2024) Advancements in artificial intelligence for medical computer-aided diagnosis. Diagnostics 14(12):1265","journal-title":"Diagnostics"},{"key":"715_CR3","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1016\/j.asoc.2017.05.043","volume":"59","author":"\u00d6F Arar","year":"2017","unstructured":"Arar \u00d6F, Ayan K (2017) A feature dependent Naive Bayes approach and its application to the software defect prediction problem. Appl Soft Comput 59:197\u2013209","journal-title":"Appl Soft Comput"},{"key":"715_CR4","first-page":"22","volume":"1","author":"SM Atnafu","year":"2021","unstructured":"Atnafu SM, Acharya AK (2021) Comparative analysis of intrusion detection attack based on machine learning classifiers. Indian J Artif Intell Neural Netw 1:22\u201328","journal-title":"Indian J Artif Intell Neural Netw"},{"key":"715_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.dajour.2022.100071","volume":"3","author":"M Bansal","year":"2022","unstructured":"Bansal M, Goyal A, Choudhary A (2022) A comparative analysis of K-nearest neighbor, genetic, support vector machine, decision tree, and long short-term memory algorithms in machine learning. Decision Analytics Journal 3:100071","journal-title":"Decision Analytics Journal"},{"key":"715_CR6","doi-asserted-by":"crossref","unstructured":"Berrar D (2019) Bayes\u2019 theorem and naive Bayes classifier, pp 403\u2013412","DOI":"10.1016\/B978-0-12-809633-8.20473-1"},{"key":"715_CR7","unstructured":"Beslin PJ et al (2023) A comprehensive survey on Naive Bayes algorithm: advantages, limitations and applications. 2023 4th International Conference on Smart Electronics and Communication (ICOSEC), IEEE"},{"key":"715_CR8","doi-asserted-by":"publisher","DOI":"10.1186\/s13634-021-00742-6","volume":"2021","author":"H Chen","year":"2021","unstructured":"Chen H et al (2021) Improved naive Bayes classification algorithm for traffic risk management. EURASIP J Adv Signal Process 2021:30","journal-title":"EURASIP J Adv Signal Process"},{"key":"715_CR12","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.swevo.2011.02.002","volume":"1","author":"J Derrac","year":"2011","unstructured":"Derrac J et al (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm and Evolutionary Computation 1:3\u201318","journal-title":"Swarm and Evolutionary Computation"},{"key":"715_CR13","unstructured":"Doewes A, Kurdhi N, Saxena A (2023) Evaluating quadratic weighted kappa as the standard performance metric for automated essay scoring. In 16th International Conference on Educational Data Mining, EDM 2023 (pp. 103-113)."},{"key":"715_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106652","volume":"96","author":"KM El Hindi","year":"2020","unstructured":"El Hindi KM, Aljulaidan RR, AlSalman H (2020) Lazy fine-tuning algorithms for na\u00efve Bayesian text classification. Appl Soft Comput 96:106652","journal-title":"Appl Soft Comput"},{"key":"715_CR15","doi-asserted-by":"publisher","first-page":"127","DOI":"10.3390\/e25010127","volume":"25","author":"C Feng","year":"2023","unstructured":"Feng C, Zhao B, Zhou X, Ding X, Shan Z (2023a) An enhanced quantum K-nearest neighbor classification algorithm based on Polar distance. Entropy 25:127","journal-title":"Entropy"},{"key":"715_CR16","doi-asserted-by":"publisher","DOI":"10.1080\/09540091.2023.2231168","volume":"35","author":"W Feng","year":"2023","unstructured":"Feng W et al (2023) An ensemble machine learning approach for classification tasks using feature generation. Connect Sci 35:2231168","journal-title":"Connect Sci"},{"key":"715_CR17","doi-asserted-by":"publisher","first-page":"833","DOI":"10.4304\/jcp.6.5.833-840","volume":"6","author":"J Gou","year":"2011","unstructured":"Gou J, Xiong T, Kuang Y (2011) A novel weighted voting for K-nearest neighbor rule. J Comput 6:833\u2013840","journal-title":"J Comput"},{"key":"715_CR18","doi-asserted-by":"publisher","first-page":"017","DOI":"10.1088\/1674-4527\/21\/1\/17","volume":"21","author":"B Han","year":"2021","unstructured":"Han B, Qiao LN, Chen JL, Zhang XD, Zhang YX, Zhao YH (2021) GeneticKNN: a weighted KNN approach supported by genetic algorithm for photometric redshift estimation of quasars. Res Astron Astrophys 21:017","journal-title":"Res Astron Astrophys"},{"key":"715_CR19","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1007\/978-981-99-7227-2_3","volume-title":"Applications of ant colony optimization and its variants: case studies and new developments","author":"A Hashemi","year":"2024","unstructured":"Hashemi A, Dowlatshahi MB (2024) Exploring ant colony optimization for feature selection: A comprehensive review. Applications of ant colony optimization and its variants: case studies and new developments. pp 45\u201360"},{"issue":"1","key":"715_CR20","doi-asserted-by":"publisher","DOI":"10.1007\/s13721-023-00420-7","volume":"12","author":"R Indu","year":"2023","unstructured":"Indu R, Dimri SC, Malik P (2023) A modified kNN algorithm to detect Parkinson\u2019s disease. Network Modeling Analysis in Health Informatics and Bioinformatics 12(1):24","journal-title":"Network Modeling Analysis in Health Informatics and Bioinformatics"},{"key":"715_CR21","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1007\/s10182-022-00439-7","volume":"106","author":"B Jahn","year":"2022","unstructured":"Jahn B et al (2022) On the role of data, statistics and decisions in a pandemic. AStA Adv Stat Anal 106:349\u2013382","journal-title":"AStA Adv Stat Anal"},{"key":"715_CR22","doi-asserted-by":"publisher","unstructured":"Jemili F, Meddeb R, Korbaa O (2023) Intrusion detection based on ensemble learning for big data classification. Cluster Computing, 27(3), 3771-3798. } https:\/\/doi.org\/10.1007\/s10586-023-04168-7}","DOI":"10.1007\/s10586-023-04168-7"},{"key":"715_CR23","first-page":"229","volume":"1","author":"G Kumar","year":"2020","unstructured":"Kumar G, Banerjee R, Singh DK, Choubey N (2020) Mathematics for machine learning. J Math Sci Comput Math 1:229\u2013238","journal-title":"J Math Sci Comput Math"},{"key":"715_CR24","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1016\/j.patrec.2020.10.005","volume":"140","author":"MM Kumbure","year":"2020","unstructured":"Kumbure MM, Luukka P, Collan M (2020) A new fuzzy k-nearest neighbor classifier based on the bonferroni mean. Pattern Recognit Lett 140:172\u2013178","journal-title":"Pattern Recognit Lett"},{"issue":"1","key":"715_CR25","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1038\/s41523-022-00438-6","volume":"8","author":"K Kumegawa","year":"2022","unstructured":"Kumegawa K, Takahashi Y, Saeki S, Yang L, Nakadai T, Osako T, Maruyama R (2022) Grhl2 motif is associated with intratumor heterogeneity of cis-regulatory elements in luminal breast cancer. NPJ Breast Cancer 8(1):70","journal-title":"NPJ Breast Cancer"},{"key":"715_CR26","doi-asserted-by":"crossref","unstructured":"Kuncheva LI (2014) Combining pattern classifiers: methods and algorithms. Wiley","DOI":"10.1002\/9781118914564"},{"key":"715_CR27","doi-asserted-by":"crossref","unstructured":"Leon F, Floria SA, B\u0103dic\u0103 C (2017) Evaluating the effect of voting methods on ensemble-based classification. 2017 IEEE Int Conf Innov Intell Syst Appl (INISTA), IEEE","DOI":"10.1109\/INISTA.2017.8001122"},{"key":"715_CR28","doi-asserted-by":"publisher","unstructured":"Little M (2008) Parkinson\u2019s. https:\/\/doi.org\/10.24432\/C59C74. UCI Machine Learning Repository","DOI":"10.24432\/C59C74"},{"key":"715_CR29","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1016\/j.ins.2018.01.025","volume":"436","author":"H Liu","year":"2018","unstructured":"Liu H, Cocea M (2018) Induction of classification rules by gini-index based rule generation. Inf Sci 436:227\u2013246","journal-title":"Inf Sci"},{"key":"715_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2020.101985","volume":"111","author":"MA Mahfouz","year":"2021","unstructured":"Mahfouz MA, Shoukry A, Ismail MA (2021) Eknn: ensemble classifier incorporating connectivity and density into kNN with application to cancer diagnosis. Artif Intell Med 111:101985","journal-title":"Artif Intell Med"},{"key":"715_CR31","doi-asserted-by":"publisher","first-page":"67","DOI":"10.4103\/aca.ACA_157_18","volume":"22","author":"P Mishra","year":"2019","unstructured":"Mishra P et al (2019) Descriptive statistics and normality tests for statistical data. Ann Card Anaesth 22:67\u201372","journal-title":"Ann Card Anaesth"},{"key":"715_CR32","doi-asserted-by":"publisher","first-page":"5713","DOI":"10.1109\/TNNLS.2018.2812279","volume":"29","author":"SS Mullick","year":"2018","unstructured":"Mullick SS, Datta S, Das S (2018) Adaptive learning-based k-nearest neighbor classifiers with resilience to class imbalance. IEEE Trans Neural Netw Learn Syst 29:5713\u20135725","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"715_CR33","unstructured":"National Institute of Diabetes and Digestive and Kidney Diseases (1990) Pima Indians Diabetes Database. Kaggle. https:\/\/www.kaggle.com\/datasets\/uciml\/pima-indians-diabetes-database"},{"key":"715_CR34","doi-asserted-by":"publisher","unstructured":"Quinlan R (1987) Thyroid disease. https:\/\/doi.org\/10.24432\/C5D010. UCI Machine Learning Repository","DOI":"10.24432\/C5D010"},{"key":"715_CR35","doi-asserted-by":"publisher","first-page":"17349","DOI":"10.1007\/s00521-023-08588-9","volume":"35","author":"AH Rabie","year":"2023","unstructured":"Rabie AH, Mohamed AM, Abo-Elsoud MA, Saleh AI (2023) A new Covid-19 diagnosis strategy using a modified KNN classifier. Neural Comput Appl 35:17349\u201317373","journal-title":"Neural Comput Appl"},{"key":"715_CR36","volume-title":"A comparison of Naive Bayes methods, logistic regression and KNN for predicting healing of Covid-19 patients in Indonesia. 2021 3rd East Indonesia","author":"MR Romadhon","year":"2021","unstructured":"Romadhon MR, Kurniawan F (2021) A comparison of Naive Bayes methods, logistic regression and KNN for predicting healing of Covid-19 patients in Indonesia. 2021 3rd East Indonesia. Conf Comput Inf Technol (EICONCIT), IEEE"},{"key":"715_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.envc.2024.100838","volume":"14","author":"N Saxena","year":"2024","unstructured":"Saxena N, Kumar R, Rao YK, Mondloe DS, Dhapekar NK, Sharma A, Yadav AS (2024) Hybrid KNN-SVM machine learning approach for solar power forecasting. Environmental Challenges 14:100838","journal-title":"Environmental Challenges"},{"key":"715_CR38","doi-asserted-by":"crossref","unstructured":"Sheskin DJ (2003) Handbook of parametric and nonparametric statistical procedures. Chapman and Hall\/CRC","DOI":"10.1201\/9781420036268"},{"key":"715_CR39","doi-asserted-by":"publisher","first-page":"687","DOI":"10.1142\/S0218001409007326","volume":"23","author":"Y Sun","year":"2009","unstructured":"Sun Y, Wong AKC, Kamel MS (2009) Classification of imbalanced data: a review. Int J Pattern Recognit Artif Intell 23:687\u2013719","journal-title":"Int J Pattern Recognit Artif Intell"},{"key":"715_CR40","doi-asserted-by":"crossref","unstructured":"Taunk K, De S, Verma S, Swetapadma A (2019) A brief review of nearest neighbor algorithm for learning and classification. 2019 Int Conf Intell Comput Control Syst (ICCS), IEEE, pp 1255\u20131260","DOI":"10.1109\/ICCS45141.2019.9065747"},{"key":"715_CR41","doi-asserted-by":"publisher","first-page":"6256","DOI":"10.1038\/s41598-022-10358-x","volume":"12","author":"S Uddin","year":"2022","unstructured":"Uddin S et al (2022) Comparative performance analysis of K-nearest neighbour (KNN) algorithm and its different variants for disease prediction. Sci Rep 12:6256","journal-title":"Sci Rep"},{"issue":"1","key":"715_CR42","doi-asserted-by":"publisher","DOI":"10.1007\/s13721-022-00391-1","volume":"11","author":"H \u00dcn\u00f6zkan","year":"2022","unstructured":"\u00dcn\u00f6zkan H, Ertem M, Bendak S (2022) Using attack graphs to defend healthcare systems from cyberattacks: a longitudinal empirical study. Netw Model Anal Health Inform Bioinform 11(1):52","journal-title":"Netw Model Anal Health Inform Bioinform"},{"key":"715_CR43","doi-asserted-by":"publisher","first-page":"2277","DOI":"10.1007\/s00500-020-05297-6","volume":"25","author":"I Wickramasinghe","year":"2021","unstructured":"Wickramasinghe I, Kalutarage H (2021) Naive bayes: applications, variations and vulnerabilities: a review of literature with code snippets for implementation. Soft Comput 25:2277\u20132293","journal-title":"Soft Comput"},{"key":"715_CR44","doi-asserted-by":"publisher","unstructured":"Wolberg W (1992) Breast cancer Wisconsin (Original). https:\/\/doi.org\/10.24432\/C5HP4Z. UCI Machine Learning Repository","DOI":"10.24432\/C5HP4Z"},{"issue":"1","key":"715_CR45","doi-asserted-by":"publisher","DOI":"10.1080\/08839514.2024.2335098","volume":"38","author":"D Yilmaz Eroglu","year":"2024","unstructured":"Yilmaz Eroglu D, Akcan U (2024) An adapted ant colony optimization for feature selection. Appl Artif Intell 38(1):2335098","journal-title":"Appl Artif Intell"},{"key":"715_CR46","doi-asserted-by":"publisher","first-page":"109554","DOI":"10.1016\/j.patcog.2023.109554","volume":"140","author":"H Zhang","year":"2023","unstructured":"Zhang H, Jiang L, Webb GI (2023) Rigorous non-disjoint discretization for Naive Bayes. Pattern Recognit 140:109554","journal-title":"Pattern Recognit"},{"key":"715_CR47","doi-asserted-by":"publisher","first-page":"108451","DOI":"10.1016\/j.knosys.2022.108451","volume":"243","author":"X Zhang","year":"2022","unstructured":"Zhang X, Xiao H, Gao R, Zhang H, Wang Y (2022) K-nearest neighbors rule combining prototype selection and local feature weighting for classification. Knowl-Based Syst 243:108451","journal-title":"Knowl-Based Syst"},{"key":"715_CR48","first-page":"20","volume":"23","author":"A Zirjam","year":"2020","unstructured":"Zirjam A, Rajebi S (2020) Applying different pattern recognition methods for identifying skin diseases. Eur J 23:20\u201323","journal-title":"Eur J"},{"key":"715_CR49","doi-asserted-by":"publisher","DOI":"10.24432\/C54598","author":"M Zwitter","year":"1988","unstructured":"Zwitter M, Soklic M (1988) Lymphography. UCI Mach Learn Repository. https:\/\/doi.org\/10.24432\/C54598","journal-title":"UCI Mach Learn Repository"}],"container-title":["Network Modeling Analysis in Health Informatics and Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13721-025-00715-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13721-025-00715-x","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13721-025-00715-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T11:58:19Z","timestamp":1767873499000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13721-025-00715-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,8]]},"references-count":46,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["715"],"URL":"https:\/\/doi.org\/10.1007\/s13721-025-00715-x","relation":{},"ISSN":["2192-6670"],"issn-type":[{"value":"2192-6670","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,8]]},"assertion":[{"value":"7 May 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 December 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 December 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 January 2026","order":4,"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 there is no conflict of interest in the present study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"32"}}