{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T18:24:04Z","timestamp":1769711044972,"version":"3.49.0"},"reference-count":32,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2023,7,2]],"date-time":"2023-07-02T00:00:00Z","timestamp":1688256000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2023,7,2]]},"abstract":"<jats:p>This article has been retracted. A retraction notice can be found at https:\/\/doi.org\/10.3233\/JIFS-219433.<\/jats:p>","DOI":"10.3233\/jifs-223265","type":"journal-article","created":{"date-parts":[[2023,5,23]],"date-time":"2023-05-23T12:20:14Z","timestamp":1684844414000},"page":"1633-1652","source":"Crossref","is-referenced-by-count":5,"title":["RETRACTED: Prediction of Breast cancer using integrated machine learning-fuzzy and dimension reduction techniques"],"prefix":"10.1177","volume":"45","author":[{"given":"Sashikanta","family":"Prusty","sequence":"first","affiliation":[{"name":"Department of Computer Science & Engineering, Siksha \u2018O\u2019 Anusandhan University, Bhubaneswar, India"}]},{"given":"Priti","family":"Das","sequence":"additional","affiliation":[{"name":"Professor & Head of the Department, Department of Pharmacology, PRM Medical College & Hospital, Baripada, Odisha, India"}]},{"given":"Sujit Kumar","family":"Dash","sequence":"additional","affiliation":[{"name":"Department of Electrical & Electronics Engineering, Siksha \u2018O\u2019 Anusandhan University, Bhubaneswar, India"}]},{"given":"Srikanta","family":"Patnaik","sequence":"additional","affiliation":[{"name":"Director of Interscience Institute of Management & Technology (IIMT), Bhubaneswar, India"}]},{"given":"Sushree Gayatri Priyadarsini","family":"Prusty","sequence":"additional","affiliation":[{"name":"Department of Computer Science & Engineering, Siksha \u2018O\u2019 Anusandhan University, Bhubaneswar, India"}]}],"member":"179","reference":[{"issue":"21","key":"10.3233\/JIFS-223265_ref1","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.1056\/NEJM199805213382101","article-title":"Incidence of hereditary nonpolyposis colorectal cancer and the feasibility of molecular screening for the disease","volume":"338","author":"Aaltonen","year":"1998","journal-title":"New England Journal of Medicine"},{"issue":"3","key":"10.3233\/JIFS-223265_ref2","first-page":"209","article-title":"Global cancer statistics: GLOBOCAN estimates incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA: A Cancer Journal for Clinicians"},{"issue":"10","key":"10.3233\/JIFS-223265_ref3","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1038\/s41571-021-00514-z","article-title":"Planning for tomorrow: Global cancer incidence and the role of prevention 2020\u20132070","volume":"18","author":"Soerjomataram","year":"2021","journal-title":"Nature Reviews Clinical Oncology"},{"issue":"1","key":"10.3233\/JIFS-223265_ref4","doi-asserted-by":"crossref","first-page":"31","DOI":"10.3233\/THC-151071","article-title":"Machine learning models in breast cancer survival prediction","volume":"24","author":"Montazeri","year":"2016","journal-title":"Technology and Health Care"},{"key":"10.3233\/JIFS-223265_ref5","doi-asserted-by":"crossref","first-page":"972421","DOI":"10.3389\/fnano.2022.972421","article-title":"SKCV: Stratified K-fold cross-validation on ML classifiers for predicting cervical cancer","volume":"4","author":"Prusty","year":"2022","journal-title":"Frontiers in Nanotechnology"},{"key":"10.3233\/JIFS-223265_ref6","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.breast.2018.03.002","article-title":"Global analysis of advanced\/metastatic breast cancer: decade report (2005\u20132015)","volume":"39","author":"Cardoso","year":"2018","journal-title":"The Breast"},{"issue":"4","key":"10.3233\/JIFS-223265_ref7","doi-asserted-by":"crossref","first-page":"pky062","DOI":"10.1093\/jncics\/pky062","article-title":"Change in survival in metastatic breast cancer with treatment advances: meta-analysis and systematic review","volume":"2","author":"Caswell-Jin","year":"2018","journal-title":"JNCI Cancer Spectrum"},{"issue":"3","key":"10.3233\/JIFS-223265_ref8","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1007\/s10549-019-05271-3","article-title":"The global prevalence of depression among breast cancer patients: a systematic review and meta-analysis","volume":"176","author":"Pilevarzadeh","year":"2019","journal-title":"Breast Cancer Research and Treatment"},{"key":"10.3233\/JIFS-223265_ref9","doi-asserted-by":"crossref","first-page":"80","DOI":"10.3389\/fgene.2019.00080","article-title":"Deep learning based analysis of histopathological images of breast cancer","volume":"10","author":"Xie","year":"2019","journal-title":"Frontiers in Genetics"},{"issue":"4","key":"10.3233\/JIFS-223265_ref11","first-page":"420","article-title":"A Review on Advanced Methodologies toIdentify the Breast Cancer Classification using the Deep LearningTechniques","volume":"22","author":"Bandaru","year":"2022","journal-title":"International Journal of Computer Science & Network Security"},{"issue":"4","key":"10.3233\/JIFS-223265_ref12","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1016\/j.jacr.2018.09.041","article-title":"Added value of radiomics on mammography for breast cancer diagnosis: a feasibility study","volume":"16","author":"Mao","year":"2019","journal-title":"Journal of the American College of Radiology"},{"issue":"1","key":"10.3233\/JIFS-223265_ref13","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1007\/s12530-019-09297-2","article-title":"Survey of deep learning in breast cancer image analysis","volume":"11","author":"Debelee","year":"2020","journal-title":"Evolving Systems"},{"key":"10.3233\/JIFS-223265_ref15","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1016\/j.procs.2020.04.064","article-title":"Breast cancer prediction using varying parameters of machine learning models","volume":"171","author":"Gupta","year":"2020","journal-title":"Procedia Computer Science"},{"issue":"2","key":"10.3233\/JIFS-223265_ref16","first-page":"132","article-title":"A model to predict breast cancer survivability using logistic regression","volume":"10","author":"Nourelahi","year":"2019","journal-title":"Middle East Journal of Cancer"},{"key":"10.3233\/JIFS-223265_ref17","doi-asserted-by":"crossref","unstructured":"Momenyan S. , Baghestani A.R. , Momenyan N. , Naseri P. and Akbari M.E. , Survival prediction of patients with breast cancer: comparisons of decision tree and logistic regression analysis, International Journal of Cancer Management 11(7) (2018).","DOI":"10.5812\/ijcm.9176"},{"issue":"2","key":"10.3233\/JIFS-223265_ref18","doi-asserted-by":"crossref","first-page":"944","DOI":"10.11591\/ijeecs.v27.i2.pp944-953","article-title":"Comparative analysis and prediction of coronary heart disease","volume":"27","author":"Prusty","year":"2022","journal-title":"Indonesian Journal of Electrical Engineering and Computer Science"},{"key":"10.3233\/JIFS-223265_ref20","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/j.procs.2018.01.125","article-title":"Optimization of K-NN algorithm by clustering and reliability coefficients: application to breast-cancer diagnosis","volume":"127","author":"Cherif","year":"2018","journal-title":"Procedia Computer Science"},{"issue":"2","key":"10.3233\/JIFS-223265_ref21","doi-asserted-by":"crossref","first-page":"815","DOI":"10.12928\/telkomnika.v18i2.14785","article-title":"Comparing random forest and support vector machines for breast cancer classification","volume":"18","author":"Aroef","year":"2020","journal-title":"TELKOMNIKA (Telecommunication Computing Electronics and Control)"},{"issue":"7","key":"10.3233\/JIFS-223265_ref22","doi-asserted-by":"crossref","first-page":"822","DOI":"10.1177\/0272989X18790963","article-title":"Comparison of logistic regression and Bayesian networks for risk prediction of breast cancer recurrence","volume":"38","author":"Witteveen","year":"2018","journal-title":"Medical Decision Making"},{"key":"10.3233\/JIFS-223265_ref23","doi-asserted-by":"crossref","first-page":"105941","DOI":"10.1016\/j.asoc.2019.105941","article-title":"An improved random forest-based rule extraction method for breast cancer diagnosis","volume":"86","author":"Wang","year":"2020","journal-title":"Applied Soft Computing"},{"key":"10.3233\/JIFS-223265_ref24","doi-asserted-by":"crossref","first-page":"103591","DOI":"10.1016\/j.jbi.2020.103591","article-title":"Detection and classification of breast cancer using logistic regression feature selection and GMDH classifier","volume":"111","author":"Khandezamin","year":"2020","journal-title":"Journal of Biomedical Informatics"},{"issue":"1","key":"10.3233\/JIFS-223265_ref25","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1149\/10701.0733ecst","article-title":"A Novel Transfer Learning Technique for Detecting Breast Cancer Mammograms Using VGG16 Bottleneck Feature","volume":"107","author":"Prusty","year":"2022","journal-title":"ECS Transactions"},{"issue":"7","key":"10.3233\/JIFS-223265_ref26","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1038\/s41416-021-01612-6","article-title":"Functional annotation of breast cancer risk loci: current progress and future directions","volume":"126","author":"Romualdo Cardoso","year":"2022","journal-title":"British Journal of Cancer"},{"key":"10.3233\/JIFS-223265_ref27","doi-asserted-by":"crossref","unstructured":"Chidambaram S. , Ganesh S.S. , Karthick A. , Jayagopal P. , Balachander B. and Manoharan S. , Diagnosing Breast Cancer Based on the Adaptive Neuro-Fuzzy Inference System, Computational and Mathematical Methods in Medicine 2022 (2022).","DOI":"10.1155\/2022\/9166873"},{"key":"10.3233\/JIFS-223265_ref28","first-page":"641","article-title":"Machine learning enabled early detection of breast cancer by structural analysis of mammograms","volume":"67","author":"Mehmood","year":"2021","journal-title":"Comput Mater Contin"},{"issue":"7","key":"10.3233\/JIFS-223265_ref29","doi-asserted-by":"crossref","first-page":"1955","DOI":"10.1007\/s40815-021-01076-z","article-title":"A novel optimization algorithm: Cascaded adaptive neuro-fuzzy inference system","volume":"23","author":"Rathnayake","year":"2021","journal-title":"International Journal of Fuzzy Systems"},{"issue":"16","key":"10.3233\/JIFS-223265_ref31","doi-asserted-by":"crossref","first-page":"10987","DOI":"10.1007\/s00500-021-05825-y","article-title":"An adaptive fuzzy inference approach for color image steganography","volume":"25","author":"Tang","year":"2021","journal-title":"Soft Computing"},{"issue":"1","key":"10.3233\/JIFS-223265_ref33","doi-asserted-by":"crossref","first-page":"13","DOI":"10.3390\/bdcc6010013","article-title":"Fuzzy neural network expert system with an improved Gini index random forest-based feature importance measure algorithm for early diagnosis of breast cancer in Saudi Arabia","volume":"6","author":"Algehyne","year":"2022","journal-title":"Big Data and Cognitive Computing"},{"issue":"8","key":"10.3233\/JIFS-223265_ref34","doi-asserted-by":"crossref","first-page":"3484","DOI":"10.3390\/app11083484","article-title":"Classification with Fuzzification Optimization Combining Fuzzy Information Systems and Type-2 Fuzzy Inference","volume":"11","author":"Tabakov","year":"2021","journal-title":"Applied Sciences"},{"issue":"1","key":"10.3233\/JIFS-223265_ref35","doi-asserted-by":"crossref","first-page":"840","DOI":"10.1080\/16583655.2021.2006894","article-title":"Numerical analysis of fractional human liver model in fuzzy environment","volume":"15","author":"Ahmad","year":"2021","journal-title":"Journal of Taibah University for Science"},{"issue":"4","key":"10.3233\/JIFS-223265_ref37","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1007\/s12553-021-00572-4","article-title":"Machine learning prediction of breast cancer survival using age, sex, length of stay, mode of diagnosis and location of cancer","volume":"11","author":"Okagbue","year":"2021","journal-title":"Health and Technology"},{"issue":"11","key":"10.3233\/JIFS-223265_ref38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1140\/epjp\/s13360-021-02178-1","article-title":"A new fuzzy fractional order model of transmission of Covid-19 with quarantine class","volume":"136","author":"Hanif","year":"2021","journal-title":"The European Physical Journal Plus"}],"updated-by":[{"DOI":"10.3233\/jifs-219433","type":"retraction","label":"Retraction","source":"retraction-watch","updated":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T00:00:00Z","timestamp":1724371200000},"record-id":"65464"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-223265","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T07:21:12Z","timestamp":1769671272000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-223265"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,2]]},"references-count":32,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.3233\/jifs-223265","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,2]]}}}