{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T14:53:28Z","timestamp":1783695208652,"version":"3.55.0"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2025,3,24]],"date-time":"2025-03-24T00:00:00Z","timestamp":1742774400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,3,24]],"date-time":"2025-03-24T00:00:00Z","timestamp":1742774400000},"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":["J Supercomput"],"DOI":"10.1007\/s11227-025-07077-1","type":"journal-article","created":{"date-parts":[[2025,3,24]],"date-time":"2025-03-24T02:52:30Z","timestamp":1742784750000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A new intelligent hybrid feature extraction model for automating cancer diagnosis: a focus on breast cancer"],"prefix":"10.1007","volume":"81","author":[{"given":"Roozbeh","family":"Rahmani","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shahin","family":"Akbarpour","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Farzan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Babak","family":"Anari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saeid Taghavi","family":"Afshord","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,3,24]]},"reference":[{"issue":"6","key":"7077_CR1","doi-asserted-by":"publisher","first-page":"524","DOI":"10.3322\/caac.21754","volume":"72","author":"AN Giaquinto","year":"2022","unstructured":"Giaquinto AN, Sung H, Miller KD, Kramer JL, Newman LA, Minihan A, Jemal A, Siegel RL (2022) Breast cancer statistics. CA Cancer J Clin 72(6):524\u2013541. https:\/\/doi.org\/10.3322\/caac.21754","journal-title":"CA Cancer J Clin"},{"key":"7077_CR2","volume":"1","author":"J Boutry","year":"1877","unstructured":"Boutry J, Tissot S, Ujvari B, Capp JP, Giraudeau M, Nedelcu AM (1877) Thomas F (2022) The evolution and ecology of benign tumors. Biochim Biophys Acta Rev Cancer 1:188643","journal-title":"Biochim Biophys Acta Rev Cancer"},{"issue":"4","key":"7077_CR3","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1080\/19393555.2022.2060879","volume":"31","author":"A Bisoyi","year":"2022","unstructured":"Bisoyi A (2022) Ownership, liability, patentability, and creativity issues in artificial intelligence. Info Securit Jurnal 31(4):377\u2013386. https:\/\/doi.org\/10.1080\/19393555.2022.2060879","journal-title":"Info Securit Jurnal"},{"key":"7077_CR4","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/B978-0-323-85240-1.00018-3","volume-title":"Computational intelligence in cancer diagnosis","author":"DSK Nayak","year":"2023","unstructured":"Nayak DSK, Mohapatra S, Al-Dabass D, Swarnkar T (2023) Deep learning approaches for high dimension cancer microarray data feature prediction: a review. Computational intelligence in cancer diagnosis. Elsevier, pp 13\u201341. https:\/\/doi.org\/10.1016\/B978-0-323-85240-1.00018-3"},{"issue":"5","key":"7077_CR5","doi-asserted-by":"publisher","first-page":"5489","DOI":"10.1007\/s12652-020-02359-3","volume":"14","author":"JG Melekoodappattu","year":"2023","unstructured":"Melekoodappattu JG, Subbian PS (2023) Automated breast cancer detection using hybrid extreme learning machine classifier. J Ambient Intell Humaniz Comput 14(5):5489\u20135498. https:\/\/doi.org\/10.1007\/s12652-020-02359-3","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"7077_CR6","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1007\/s10044-018-0760-x","volume":"22","author":"R Chaieb","year":"2018","unstructured":"Chaieb R, Kalti K (2018) Feature subset selection for classification of malignant and benign breast masses in digital mammography. Pattern Anal Appl 22:803\u2013829","journal-title":"Pattern Anal Appl"},{"issue":"1","key":"7077_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12880-023-00964-0","volume":"23","author":"MM Srikantamurthy","year":"2023","unstructured":"Srikantamurthy MM, Rallabandi VPS, Dudekula DB, Natarajan S, Park J (2023) Classification of benign and malignant subtypes of breast cancer histopathology imaging using hybrid CNN-LSTM based transfer learning. BMC Med Imag 23(1):1\u201315","journal-title":"BMC Med Imag"},{"key":"7077_CR8","doi-asserted-by":"publisher","first-page":"117605","DOI":"10.1016\/j.eswa.2022.117695","volume":"205","author":"MA Talukder","year":"2022","unstructured":"Talukder MA, Islam MM, Uddin MA, Akhter A, Hasan KF, Moni MA (2022) Machine learning-based lung and colon cancer detection using deep feature extraction and ensemble learning. Expert System Application 205:117605","journal-title":"Expert System Application"},{"key":"7077_CR9","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1007\/978-981-19-9819-5_37","volume-title":"Computational Vision and bio-inspired computing: proceedings of ICCVBIC 2022","author":"S Gupta","year":"2023","unstructured":"Gupta S, Agrawal S, Singh SK, Kumar S (2023) A novel transfer learning-based model for ultrasound breast cancer image classification. In: Smys S, Jo\u00e3o MR, Tavares S, Shi F (eds) Computational Vision and bio-inspired computing: proceedings of ICCVBIC 2022. Springer Nature Singapore, Singapore, pp 511\u2013523. https:\/\/doi.org\/10.1007\/978-981-19-9819-5_37"},{"key":"7077_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2020.106958","volume":"90","author":"S Punitha","year":"2021","unstructured":"Punitha S, Turjman FA, Stephan T (2021) An automated breast cancer diagnosis using feature selection and parameter optimization in ANN. Comput Electr Eng 90:106958","journal-title":"Comput Electr Eng"},{"issue":"5","key":"7077_CR11","doi-asserted-by":"publisher","first-page":"153","DOI":"10.3390\/fi14050153","volume":"14","author":"RO Ogundokun","year":"2022","unstructured":"Ogundokun RO, Misra S, Douglas M, Dama\u0161evi\u010dius R, Maskeli\u016bnas R (2022) Medical Internet-of-Things based breast cancer diagnosis using hyperparameter-optimized neural networks. Future Internet 14(5):153","journal-title":"Future Internet"},{"key":"7077_CR12","doi-asserted-by":"publisher","first-page":"87694","DOI":"10.1109\/ACCESS.2023.3304628","volume":"11","author":"S Sharmin","year":"2023","unstructured":"Sharmin S, Tanvir Ahammad Md, Talukder A, Ghose P (2023) A hybrid dependable deep feature extraction and ensemble-based machine learning approach for breast cancer detection. IEEE Access 11:87694\u201387708. https:\/\/doi.org\/10.1109\/ACCESS.2023.3304628","journal-title":"IEEE Access"},{"key":"7077_CR13","doi-asserted-by":"publisher","DOI":"10.1007\/s42452-023-05339-2","author":"I Keshta","year":"2023","unstructured":"Keshta I, Deshpande PS, Shabaz M (2023) Multi-stage biomedical feature selection extraction algorithm for cancer detection. SN Appl. https:\/\/doi.org\/10.1007\/s42452-023-05339-2","journal-title":"SN Appl"},{"issue":"12","key":"7077_CR14","doi-asserted-by":"publisher","first-page":"3075","DOI":"10.3390\/cancers15123075","volume":"15","author":"H Kode","year":"2024","unstructured":"Kode H, Barkana BD (2024) Deep Learning- and Expert Knowledge-Based Feature Extraction and Performance Evaluation in Breast Histopathology Images. Cancers (Basel) 15(12):3075. https:\/\/doi.org\/10.3390\/cancers15123075","journal-title":"Cancers (Basel)"},{"key":"7077_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2020.101845","volume":"105","author":"ED Carvalho","year":"2020","unstructured":"Carvalho ED, Filho AOC, Silva RRV, Ara\u00fajo FHD, Diniz JOB, Silva AC, Paiva AC, Gattass M (2020) Breast cancer diagnosis from histopathological images using textural features and CBIR. Artif Intell Med 105:101845","journal-title":"Artif Intell Med"},{"key":"7077_CR16","unstructured":"Chandana CH, Krishna GB (2021) Breast cancer detection using random forest classifier. Materials Today: Proceedings"},{"key":"7077_CR17","doi-asserted-by":"publisher","first-page":"14055","DOI":"10.1007\/s11042-022-13807-x","volume":"82","author":"Y Sahu","year":"2023","unstructured":"Sahu Y, Tripathi A, Gupta RK (2023) A CNN-SVM based computer aided diagnosis of breast Cancer using histogram K-means segmentation technique. Multimedia Tools Applications 82:14055\u201314075. https:\/\/doi.org\/10.1007\/s11042-022-13807-x","journal-title":"Multimedia Tools Applications"},{"key":"7077_CR18","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1007\/s42979-022-01129-6","volume":"3","author":"I AlShorbajit","year":"2022","unstructured":"AlShorbajit I, Kachare P, Zogaan W (2022) Learning features using an optimized artificial neural network for breast cancer diagnosis. SN COMPUT SCI 3:229. https:\/\/doi.org\/10.1007\/s42979-022-01129-6","journal-title":"SN COMPUT SCI"},{"issue":"2","key":"7077_CR19","first-page":"1","volume":"86","author":"NK Younis","year":"2022","unstructured":"Younis NK, Roumieh R, Bassil EP, Ghoubaira JA, Kobeissy F, Eid AH (2022) Nanoparticles: attractive tools to treat colorectal cancer. Seminars in Cancer Biology journal 86(2):1\u201313","journal-title":"Seminars in Cancer Biology journal"},{"key":"7077_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.107023","volume":"161","author":"A Isosalo","year":"2023","unstructured":"Isosalo A, Inkinen SI, Turunen T, Ipatti PS, Reponen J, Nieminen MT (2023) Independent evaluation of a multi-view multi-task convolutional neural network breast cancer classification model using Finnish mammography screening data. Comput Biol Med 161:107023","journal-title":"Comput Biol Med"},{"key":"7077_CR21","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1007\/s12539-021-00467-y","volume":"14","author":"T Kavitha","year":"2022","unstructured":"Kavitha T, Mathai PP, Karthikeyan C (2022) Deep Learning Based Capsule Neural Network Model for Breast Cancer Diagnosis Using Mammogram Images. Interdiscip Sci Comput Life Sci 14:113\u2013129. https:\/\/doi.org\/10.1007\/s12539-021-00467-y","journal-title":"Interdiscip Sci Comput Life Sci"},{"key":"7077_CR22","doi-asserted-by":"publisher","unstructured":"Alickovic E, Subasi A (2020) Normalized Neural Networks for Breast Cancer Classification. In International Conference on Medical and Biological Engineering. pp. 519\u2013524. https:\/\/doi.org\/10.1007\/978-3-030-17971-7-77","DOI":"10.1007\/978-3-030-17971-7-77"},{"key":"7077_CR23","doi-asserted-by":"publisher","first-page":"8581","DOI":"10.1007\/s11042-022-13550-3","volume":"82","author":"D Singh","year":"2023","unstructured":"Singh D, Nigam R, Mittal R (2023) Information retrieval using machine learning from breast cancer diagnosis. Multimedia Tools Applicatios 82:8581\u20138602. https:\/\/doi.org\/10.1007\/s11042-022-13550-3","journal-title":"Multimedia Tools Applicatios"},{"key":"7077_CR24","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1007\/s10044-018-0760-x","volume":"22","author":"R Chaieb","year":"2019","unstructured":"Chaieb R, Kalti K (2019) Feature subset selection for classification of malignant and benign breast masses in digital mammography. Pattern Anal Applic 22:803\u2013829. https:\/\/doi.org\/10.1007\/s10044-018-0760-x","journal-title":"Pattern Anal Applic"},{"key":"7077_CR25","first-page":"76","volume-title":"Digital image processing","author":"RC Gonzalez","year":"2002","unstructured":"Gonzalez RC, Woods RE (2002) Digital image processing. Prentice- Hall Inc, New Jersey, pp 76\u2013142"},{"key":"7077_CR26","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1016\/S0146-664X(75)80008-6","volume":"4","author":"MM Galloway","year":"1975","unstructured":"Galloway MM (1975) Texture classification using gray level run length. Computing Graph Image Process 4:172\u2013179","journal-title":"Computing Graph Image Process"},{"issue":"6","key":"7077_CR27","doi-asserted-by":"publisher","first-page":"460","DOI":"10.1109\/TSMC.1978.4309999","volume":"8","author":"H Tamura","year":"1978","unstructured":"Tamura H, Mori S, Yamawaki T (1978) Texture features corresponding to visual perception. IEEE Trans Syst Man Cybernet Smc 8(6):460\u2013473. https:\/\/doi.org\/10.1109\/TSMC.1978.4309999","journal-title":"IEEE Trans Syst Man Cybernet Smc"},{"issue":"8","key":"7077_CR28","doi-asserted-by":"publisher","first-page":"837","DOI":"10.1109\/34.531803","volume":"18","author":"BS Manjunath","year":"1996","unstructured":"Manjunath BS, Ma WY (1996) Texture features for browsing and retrieval of large image data. IEEE Trans Pattern Anal Mach Intell (Spec Issue Digit Library) 18(8):837\u2013842. https:\/\/doi.org\/10.1109\/34.531803","journal-title":"IEEE Trans Pattern Anal Mach Intell (Spec Issue Digit Library)"},{"key":"7077_CR29","unstructured":"Rodrigues JF Jr, Traina AJM, Traina C Jr (2005) Enhanced visual evaluation of feature extractors for image mining. In: The 3rd ACS\/IEEE International Conference on Computer Systems and Applications"},{"key":"7077_CR30","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1016\/j.patcog.2005.07.006","volume":"39","author":"HD Cheng","year":"2006","unstructured":"Cheng HD, Shi XJ, Min R, Hu LM, Cai XP, Du HN (2006) Approaches for automated detection and classification of masses in mammograms. Pattern Recognit 39:646\u2013668","journal-title":"Pattern Recognit"},{"issue":"8","key":"7077_CR31","doi-asserted-by":"publisher","first-page":"1226","DOI":"10.1109\/TPAMI.2005.159","volume":"27","author":"H Peng","year":"2005","unstructured":"Peng H, Long F, Ding C (2005) Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans Pattern Anal Mach Intelligence 27(8):1226\u20131238. https:\/\/doi.org\/10.1109\/TPAMI.2005.159","journal-title":"IEEE Trans Pattern Anal Mach Intelligence"},{"key":"7077_CR32","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1016\/j.bspc.2018.10.010","volume":"48","author":"W Ayadi","year":"2019","unstructured":"Ayadi W, Elhamzi W, Charfi I, Atri M (2019) A hybrid feature extraction approach for brain MRI classification based on Bag-of-words. Biomed Signal Process Control 48:144\u2013152. https:\/\/doi.org\/10.1016\/j.bspc.2018.10.010","journal-title":"Biomed Signal Process Control"},{"key":"7077_CR33","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.compbiomed.2015.06.012","volume":"64","author":"S Dhahbi","year":"2015","unstructured":"Dhahbi S, Barhoumi W, Zagrouba E (2015) Breast cancer diagnosis in digitized mammograms using curvelet moments. Comput Biol Med 64:79\u201390","journal-title":"Comput Biol Med"},{"key":"7077_CR34","doi-asserted-by":"publisher","first-page":"11039","DOI":"10.1007\/s12652-022-04384-w","volume":"14","author":"H Mojez","year":"2023","unstructured":"Mojez H, Bidgoli AM, Javadi HHS (2023) Extended array model of star capacity-aware delay-based next controller placement problem for multiple controller failures in software-defined wide area networks. J Ambient Intell Human Comput 14:11039\u201311057. https:\/\/doi.org\/10.1007\/s12652-022-04384-w","journal-title":"J Ambient Intell Human Comput"},{"key":"7077_CR35","doi-asserted-by":"publisher","first-page":"13205","DOI":"10.1007\/s11227-022-04360-3","volume":"78","author":"H Mojez","year":"2022","unstructured":"Mojez H, Bidgoli AM, Javadi HHS (2022) Star capacity-aware latency-based next controller placement problem with considering single controller failure in software-defined wide-area networks. J Supercomput 78:13205\u201313244. https:\/\/doi.org\/10.1007\/s11227-022-04360-3","journal-title":"J Supercomput"},{"key":"7077_CR36","doi-asserted-by":"publisher","first-page":"1818","DOI":"10.1016\/j.patrec.2007.05.018","volume":"28","author":"S Manocha","year":"2007","unstructured":"Manocha S, Girolami M (2007) An empirical analysis of the probabilistic k-nearest neighbor classifier. Pattern Recognit Lett 28:1818\u20131824. https:\/\/doi.org\/10.1016\/j.patrec.2007.05.018","journal-title":"Pattern Recognit Lett"},{"key":"7077_CR37","unstructured":"Suckling J (1994) The Mammographic Image Analysis Society Digital Mammogram\u00a0Database. Exerpta Medica International Congress. pp. 375\u2013378."},{"key":"7077_CR38","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2017.177","volume":"4","author":"R Lee","year":"2017","unstructured":"Lee R, Gimenez F, Hoogi A (2017) A curated mammography data set for use in computer-aided detection and diagnosis research. Sci Data 4:170177. https:\/\/doi.org\/10.1038\/sdata.2017.177","journal-title":"Sci Data"},{"issue":"11","key":"7077_CR39","doi-asserted-by":"publisher","first-page":"2971","DOI":"10.3390\/biomedicines10112971","volume":"10","author":"RM Al-Tam","year":"2022","unstructured":"Al-Tam RM, Al-Hejri AM, Narangale SM, Samee NA, Mahmoud NF, Al-masni MA, Al-antari MA (2022) A hybrid workflow of residual convolutional transformer encoder for breast cancer classification using digital X-ray mammograms. Biomedicines 10(11):2971. https:\/\/doi.org\/10.3390\/biomedicines10112971","journal-title":"Biomedicines"},{"key":"7077_CR40","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1016\/j.compmedimag.2007.02.004","volume":"31","author":"Q Li","year":"2007","unstructured":"Li Q (2007) Improvement of bias and generalizability for computer-aided diagnostic schemes. Computing Med Imaging Gr 31:338\u2013345. https:\/\/doi.org\/10.1016\/j.compmedimag.2007.02.004","journal-title":"Computing Med Imaging Gr"},{"issue":"1","key":"7077_CR41","doi-asserted-by":"publisher","first-page":"89","DOI":"10.3390\/diagnostics13010089","volume":"13","author":"AM Al-Hejri","year":"2023","unstructured":"Al-Hejri AM, Al-Tam RM, Fazea M, Sable AH, Lee S, Al-antari MA (2023) ETECADx: Ensemble Self-Attention Transformer Encoder for Breast Cancer Diagnosis Using Full-Field Digital X-ray Breast Images. Diagnostics 13(1):89. https:\/\/doi.org\/10.3390\/diagnostics13010089","journal-title":"Diagnostics"},{"key":"7077_CR42","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1007\/s10462-023-10631-z","volume":"57","author":"R Archana","year":"2024","unstructured":"Archana R, Jeevaraj PSE (2024) Deep learning models for digital image processing: a review. Artif Intell Rev 57:11. https:\/\/doi.org\/10.1007\/s10462-023-10631-z","journal-title":"Artif Intell Rev"},{"key":"7077_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2020.106854","volume":"149","author":"L Li","year":"2020","unstructured":"Li L, Fan Y, Tse M, Lin KY (2020) A review of applications in federated learning. Comput Ind Eng 149:106854","journal-title":"Comput Ind Eng"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07077-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-025-07077-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07077-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,24]],"date-time":"2025-03-24T02:52:56Z","timestamp":1742784776000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-025-07077-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,24]]},"references-count":43,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2025,4]]}},"alternative-id":["7077"],"URL":"https:\/\/doi.org\/10.1007\/s11227-025-07077-1","relation":{},"ISSN":["1573-0484"],"issn-type":[{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,24]]},"assertion":[{"value":"14 February 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 March 2025","order":2,"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 no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interests"}}],"article-number":"651"}}