{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T18:23:15Z","timestamp":1778696595058,"version":"3.51.4"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"35","license":[{"start":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T00:00:00Z","timestamp":1726876800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T00:00:00Z","timestamp":1726876800000},"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":["Neural Comput & Applic"],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1007\/s00521-024-10235-w","type":"journal-article","created":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T09:01:41Z","timestamp":1726909301000},"page":"22403-22416","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A novel K-nearest neighbor classifier for lung cancer disease diagnosis"],"prefix":"10.1007","volume":"36","author":[{"given":"Ravi Kumar","family":"Sachdeva","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Priyanka","family":"Bathla","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pooja","family":"Rani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rohit","family":"Lamba","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"G. S. Pradeep","family":"Ghantasala","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8123-2238","authenticated-orcid":false,"given":"Ibrahim F.","family":"Nassar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,9,21]]},"reference":[{"issue":"1","key":"10235_CR1","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1165\/rcmb.2018-0416TR","volume":"61","author":"HB Schiller","year":"2019","unstructured":"Schiller HB, Montoro DT, Simon LM, Rawlins EL, Meyer KB, Strunz M, Braga FAV, Timens W, Koppelman GH, Budinger GRS, Burgess JK (2019) The human lung cell atlas: a high-resolution reference map of the human lung in health and disease. Am J Respir Cell Mol Biol 61(1):31\u201341. https:\/\/doi.org\/10.1165\/rcmb.2018-0416TR","journal-title":"Am J Respir Cell Mol Biol"},{"key":"10235_CR2","doi-asserted-by":"publisher","first-page":"1263","DOI":"10.3389\/fimmu.2019.01263","volume":"10","author":"B Hervier","year":"2019","unstructured":"Hervier B, Russick J, Cremer I, Vieillard V (2019) NK cells in the human lungs. Front Immunol 10:1263. https:\/\/doi.org\/10.3389\/fimmu.2019.01263","journal-title":"Front Immunol"},{"issue":"4","key":"10235_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/bdcc6040139","volume":"6","author":"E Dritsas","year":"2022","unstructured":"Dritsas E, Trigka M (2022) Lung cancer risk prediction with machine learning models. Big Data Cognit Comput 6(4):1\u201314. https:\/\/doi.org\/10.3390\/bdcc6040139","journal-title":"Big Data Cognit Comput"},{"key":"10235_CR4","doi-asserted-by":"publisher","unstructured":"Hsu CH, Manogaran G, Panchatcharam P, Vivekanandan S (2018) A new approach for prediction of lung carcinoma using back propagation neural network with decision tree classifiers. In: 2018 IEEE 8th international symposium on cloud and service computing (SC2), pp. 111\u2013115.IEEE. https:\/\/doi.org\/10.1109\/SC2.2018.00023","DOI":"10.1109\/SC2.2018.00023"},{"issue":"2","key":"10235_CR5","doi-asserted-by":"publisher","first-page":"141","DOI":"10.48161\/qaj.v1n2a58","volume":"1","author":"DM Abdullah","year":"2021","unstructured":"Abdullah DM, Abdulazeez AM, Sallow AB (2021) Lung cancer prediction and classification based on correlation selection method using machine learning techniques. Qubahan Acad J 1(2):141\u2013149. https:\/\/doi.org\/10.48161\/qaj.v1n2a58","journal-title":"Qubahan Acad J"},{"key":"10235_CR6","doi-asserted-by":"publisher","unstructured":"Patra R (2020) Prediction of lung cancer using machine learning classifier. In: international conference on computing science, communication and security, pp. 132\u2013142. Springer. https:\/\/doi.org\/10.1007\/978-981-15-6648-6_11","DOI":"10.1007\/978-981-15-6648-6_11"},{"key":"10235_CR7","doi-asserted-by":"publisher","unstructured":"Sachdeva RK, Garg T, Khaira GS, Mitrav D, Ahuja R (2022) A systematic method for lung cancer classification. In: 2022 10th international conference on reliability, infocom technologies and optimization (trends and future directions) (ICRITO), pp. 1\u20135. IEEE. https:\/\/doi.org\/10.1109\/ICRITO56286.2022.9964778","DOI":"10.1109\/ICRITO56286.2022.9964778"},{"key":"10235_CR8","doi-asserted-by":"publisher","unstructured":"Radhika P, Nair RA, Veena GA (2019) Comparative study of lung cancer detection using machine learning algorithms. In: 2019 IEEE international conference on electrical, computer and communication technologies (ICECCT), pp. 1\u20134. IEEE. https:\/\/doi.org\/10.1109\/ICECCT.2019.8869001","DOI":"10.1109\/ICECCT.2019.8869001"},{"key":"10235_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3389\/frai.2022.826374","volume":"5","author":"MA Mezher","year":"2022","unstructured":"Mezher MA, Altamimi A, Altamimi R (2022) A genetic folding strategy based support vector machine to optimize lung cancer classification. Front Artif Intell 5:1\u20137. https:\/\/doi.org\/10.3389\/frai.2022.826374","journal-title":"Front Artif Intell"},{"key":"10235_CR10","doi-asserted-by":"publisher","unstructured":"Rajalaxmi R, Kavithra S, Gothai E, Natesan P, Thamilselvan R (2022) A Systematic Review Of Lung Cancer Prediction Using Machine Learning Algorithm. In: 2022 International conference on computer communication and informatics (ICCCI), pp. 1\u20137. IEEE. https:\/\/doi.org\/10.1109\/ICCCI54379.2022.9740809","DOI":"10.1109\/ICCCI54379.2022.9740809"},{"key":"10235_CR11","doi-asserted-by":"publisher","unstructured":"Sebastian AM, Peter D (2023), Identifying the predictors from lung cancer data using machine learning. In: Sentiment analysis and deep learning, pp. 691\u2013701, Springer Nature Singapore. https:\/\/doi.org\/10.1007\/978-981-19-5443-6_53. https:\/\/doi.org\/10.1007\/978-981-19-5443-6_53","DOI":"10.1007\/978-981-19-5443-6_53 10.1007\/978-981-19-5443-6_53"},{"key":"10235_CR12","doi-asserted-by":"publisher","DOI":"10.2245\/mjcs.sp2022no1.10","author":"TR Ramesh","year":"2022","unstructured":"Ramesh TR, Lilhore UK, Poongodi M, Simaiya S, Kaur A, Hamdi M (2022) Predictive analysis of heart diseases with machine learning approaches. Malays J Comput Sci. https:\/\/doi.org\/10.2245\/mjcs.sp2022no1.10","journal-title":"Malays J Comput Sci"},{"issue":"9","key":"10235_CR13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.35940\/ijitee.E2931.078919","volume":"8","author":"K Verma","year":"2019","unstructured":"Verma K, Bhardwaj S, Arya R, Islam UL, Bhushan M, Kumar A, Samant P (2019) Latest tools for data mining and machine learning. Int J Innov Technol Explor Eng 8(9):1\u20136","journal-title":"Int J Innov Technol Explor Eng"},{"issue":"2","key":"10235_CR14","doi-asserted-by":"publisher","first-page":"1007","DOI":"10.32604\/iasc.2022.019778","volume":"31","author":"AK Dutta","year":"2022","unstructured":"Dutta AK (2022) Detecting lung cancer using machine learning techniques. Int Autom Soft Comput 31(2):1007\u20131023","journal-title":"Int Autom Soft Comput"},{"issue":"6","key":"10235_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/ICECCT.2019.8869001","volume":"6","author":"S Jaiswal","year":"2022","unstructured":"Jaiswal S, Deshmukh R, Meshram N, Deshpande A, Wakode PB (2022) A comparative study of lung cancer detection using machine learning algorithms. Int J Sci Res Eng Manag 6(6):1\u20136. https:\/\/doi.org\/10.1109\/ICECCT.2019.8869001","journal-title":"Int J Sci Res Eng Manag"},{"issue":"4","key":"10235_CR16","first-page":"3198","volume":"9","author":"A Asuntha","year":"2016","unstructured":"Asuntha A, Brindha A, Indirani S, Srinivasan A (2016) Lung cancer detection using SVM algorithm and optimization techniques. J Chem Pharm Sci 9(4):3198\u20133203","journal-title":"J Chem Pharm Sci"},{"key":"10235_CR17","doi-asserted-by":"publisher","unstructured":"Manju BR, Athira V, Rajendran A (2020) Efficient multi-level lung cancer prediction model using support vector machine classifier. In: International conference on robotics, intelligent automation and control technologies, pp. 1\u201314, IOP publishing. https:\/\/doi.org\/10.1088\/1757-899X\/1012\/1\/012034","DOI":"10.1088\/1757-899X\/1012\/1\/012034"},{"issue":"4","key":"10235_CR18","doi-asserted-by":"publisher","first-page":"2617","DOI":"10.1007\/s11063-020-10192-0","volume":"53","author":"S Shanthi","year":"2021","unstructured":"Shanthi S, Rajkumar N (2021) Lung cancer prediction using stochastic diffusion search (SDS) based feature selection and machine learning methods. Neural Process Lett 53(4):2617\u20132630. https:\/\/doi.org\/10.1007\/s11063-020-10192-0","journal-title":"Neural Process Lett"},{"issue":"1","key":"10235_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-021-04608-7","volume":"12","author":"B Alsinglawi","year":"2022","unstructured":"Alsinglawi B, Alshari O, Alorjani M, Mubin O, Alnajjar F, Novoa M, Darwish O (2022) An explainable machine learning framework for lung cancer hospital length of stay prediction. Sci Rep 12(1):1\u201310. https:\/\/doi.org\/10.1038\/s41598-021-04608-7","journal-title":"Sci Rep"},{"key":"10235_CR20","doi-asserted-by":"publisher","first-page":"412","DOI":"10.1016\/j.procs.2018.05.162","volume":"132","author":"K Pradeep","year":"2018","unstructured":"Pradeep K, Naveen N (2018) Lung cancer survivability prediction based on performance using classification techniques of support vector machines, C4. 5 and Naive Bayes algorithms for healthcare analytics. Procedia Comput Sci 132:412\u2013420. https:\/\/doi.org\/10.1016\/j.procs.2018.05.162","journal-title":"Procedia Comput Sci"},{"key":"10235_CR21","doi-asserted-by":"crossref","unstructured":"Pradhan M (2023) An early diagnosis of lung nodule using CT images based on hybrid machine learning techniques. In: Machine learning and artificial intelligence in healthcare systems, pp. 311\u2013329, CRC Press.","DOI":"10.1201\/9781003265436-14"},{"issue":"2","key":"10235_CR22","doi-asserted-by":"publisher","first-page":"91","DOI":"10.12720\/jait.11.2.91-96","volume":"11","author":"K Tuncal","year":"2020","unstructured":"Tuncal K, Sekeroglu B, Ozkan C (2020) Lung cancer incidence prediction using machine learning algorithms. J Adv Inform Technol 11(2):91\u201396","journal-title":"J Adv Inform Technol"},{"key":"10235_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3389\/fonc.2019.01393","volume":"9","author":"DA Delzell","year":"2019","unstructured":"Delzell DA, Magnuson S, Peter T, Smith M, Smith BJ (2019) Machine learning and feature selection methods for disease classification with application to lung cancer screening image data. Front Oncol 9:1\u20138. https:\/\/doi.org\/10.3389\/fonc.2019.01393","journal-title":"Front Oncol"},{"issue":"8","key":"10235_CR24","doi-asserted-by":"publisher","first-page":"1777","DOI":"10.1109\/TMI.2019.2894349","volume":"38","author":"S Hussein","year":"2019","unstructured":"Hussein S, Kandel P, Bolan CW, Wallace MB, Bagci U (2019) Lung and pancreatic tumor characterization in the deep learning era: novel supervised and unsupervised learning approaches. IEEE Trans Med Imaging 38(8):1777\u20131787. https:\/\/doi.org\/10.1109\/TMI.2019.2894349","journal-title":"IEEE Trans Med Imaging"},{"key":"10235_CR25","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.procs.2017.12.016","volume":"125","author":"S Makaju","year":"2018","unstructured":"Makaju S, Prasad P, Alsadoon A, Singh A, Elchouemi A (2018) Lung cancer detection using CT scan images. Procedia Comput Sci 125:107\u2013114. https:\/\/doi.org\/10.1016\/j.procs.2017.12.016","journal-title":"Procedia Comput Sci"},{"issue":"21","key":"10235_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/cancers14215457","volume":"14","author":"I Shafi","year":"2022","unstructured":"Shafi I, Din S, Khan A, D\u00edez IDLT, Pali-Casanova R, Tutusaus K, Ashraf I (2022) An effective method for lung cancer diagnosis from CT scan using deep learning-based support vector network. Cancers 14(21):1\u201318. https:\/\/doi.org\/10.3390\/cancers14215457","journal-title":"Cancers"},{"key":"10235_CR27","unstructured":"Lung Cancer DataSet. Available: https:\/\/www.kaggle.com\/datasets\/mysarahmadbhat\/lung-cancer"},{"key":"10235_CR28","doi-asserted-by":"publisher","unstructured":"Tiwari H (2022) Early prediction of heart disease using deep learning approach. In: Deep Learning for Medical Applications with Unique Data, pp. 107\u2013122, Academic Press. https:\/\/doi.org\/10.1016\/B978-0-12-824145-5.00014-9","DOI":"10.1016\/B978-0-12-824145-5.00014-9"},{"key":"10235_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.compbiomed.2021.104431","volume":"134","author":"W Ksi\u0105\u017cek","year":"2021","unstructured":"Ksi\u0105\u017cek W, Gandor M, P\u0142awiak P (2021) Comparison of various approaches to combine logistic regression with genetic algorithms in survival prediction of hepatocellular carcinoma. Comput Biol Med 134:1\u201313. https:\/\/doi.org\/10.1016\/j.compbiomed.2021.104431","journal-title":"Comput Biol Med"},{"issue":"1","key":"10235_CR30","doi-asserted-by":"publisher","first-page":"10","DOI":"10.38094\/jastt20179","volume":"2","author":"I Mahmood","year":"2021","unstructured":"Mahmood I, Abdulazeez AM (2021) The role of machine learning algorithms for diagnosing diseases. J Appl Sci Technol Trends 2(1):10\u201319. https:\/\/doi.org\/10.38094\/jastt20179","journal-title":"J Appl Sci Technol Trends"},{"key":"10235_CR31","doi-asserted-by":"publisher","unstructured":"Islam MJ, Wu QMJ, Ahmadi M, Sid-Ahmed MA (2007). Investigating the performance of naive- bayes classifiers and K- nearest neighbor classifiers. In: 2007 International conference on convergence information technology (ICCIT 2007), pp. 1541\u20131546, IEEE(2007). https:\/\/doi.org\/10.1109\/ICCIT.2007.148.","DOI":"10.1109\/ICCIT.2007.148"},{"issue":"6","key":"10235_CR32","doi-asserted-by":"publisher","first-page":"775","DOI":"10.1016\/j.knosys.2011.02.014","volume":"24","author":"D Soria","year":"2011","unstructured":"Soria D, Garibaldi JM, Ambrogi F, Biganzoli EM, Ellis IO (2011) A \u201cnon-parametric\u201d version of the naive Bayes classifier. Knowl-Based Syst 24(6):775\u2013784. https:\/\/doi.org\/10.1016\/j.knosys.2011.02.014","journal-title":"Knowl-Based Syst"},{"issue":"2","key":"10235_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4018\/IJISMD.2021040102","volume":"12","author":"P Rani","year":"2021","unstructured":"Rani P, Kumar R, Jain A, Chawla SK (2021) A hybrid approach for feature selection based on genetic algorithm and recursive feature elimination. Int J Inform Syst Model Design 12(2):1\u201312. https:\/\/doi.org\/10.4018\/IJISMD.2021040102","journal-title":"Int J Inform Syst Model Design"},{"issue":"12","key":"10235_CR34","first-page":"924","volume":"6","author":"MS Sri","year":"2019","unstructured":"Sri MS (2019) A review on object tracking based on KNN classifier. Int Res J Eng Technol 6(12):924\u2013927","journal-title":"Int Res J Eng Technol"},{"key":"10235_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113829","volume":"162","author":"Z Geler","year":"2020","unstructured":"Geler Z, Kurbalija V, Ivanovic M, Radovanovi\u0107 M (2020) Weighted kNN and constrained elastic distances for time-series classification. Expert Syst Appl 162:113829. https:\/\/doi.org\/10.1016\/j.eswa.2020.113829","journal-title":"Expert Syst Appl"},{"key":"10235_CR36","doi-asserted-by":"publisher","unstructured":"Sachdeva RK, Singh KD, Sharma S, Bathla P, & Solanki V (2023). An organized method for heart failure classification. In 2023 international conference on emerging smart computing and informatics (ESCI) (pp. 1\u20136). IEEE. https:\/\/doi.org\/10.1109\/ESCI56872.2023.10099809.","DOI":"10.1109\/ESCI56872.2023.10099809"},{"key":"10235_CR37","doi-asserted-by":"publisher","unstructured":"Rani P, Lamba R, Sachdeva RK, Bathla P, & Aledaily AN (2023). Diabetes prediction using machine learning classification algorithms. In 2023 international conference on smart computing and application (ICSCA) (pp. 1\u20135). IEEE. https:\/\/doi.org\/10.1109\/ICSCA57840.2023.10087827","DOI":"10.1109\/ICSCA57840.2023.10087827"},{"key":"10235_CR38","doi-asserted-by":"publisher","unstructured":"Sachdeva RK, Singh KD, Bathla P, Jain A, Choudhury T, & Kotecha K (2023). Empowering hepatitis diagnosis using RFE feature selection. In 2023 7th international symposium on multidisciplinary studies and innovative technologies (ISMSIT) (pp. 1\u20135). IEEE. https:\/\/doi.org\/10.1109\/ISMSIT58785.2023.10304999","DOI":"10.1109\/ISMSIT58785.2023.10304999"},{"key":"10235_CR39","unstructured":"Lung Cancer Data. Available: https:\/\/data.world\/cancerdatahp\/lung-cancer-data"},{"key":"10235_CR40","unstructured":"Stroke Prediction Dataset. Available: https:\/\/www.kaggle.com\/datasets\/fedesoriano\/stroke-prediction-dataset"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10235-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-10235-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10235-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,25]],"date-time":"2024-11-25T12:06:47Z","timestamp":1732536407000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-10235-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,21]]},"references-count":40,"journal-issue":{"issue":"35","published-print":{"date-parts":[[2024,12]]}},"alternative-id":["10235"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-10235-w","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,21]]},"assertion":[{"value":"26 December 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 July 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 September 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}