{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T20:10:44Z","timestamp":1782418244497,"version":"3.54.5"},"reference-count":27,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2023,2,21]],"date-time":"2023-02-21T00:00:00Z","timestamp":1676937600000},"content-version":"vor","delay-in-days":51,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["BioMed Research International"],"published-print":{"date-parts":[[2023,1]]},"abstract":"<jats:p>Cancer is characterized by abnormal cell growth and proliferation, which are both diagnostic indicators of the disease. When cancerous cells enter one organ, there is a risk that they may spread to adjacent tissues and eventually to other organs. Cancer of the cervix of the uterus often initially manifests itself in the uterine cervix, which is located at the very bottom of the uterus. Both the growth and death of cervical cells are characteristic features of this condition. False\u2010negative results provide a significant moral dilemma since they may cause women to get an incorrect diagnosis of cancer, which in turn can result in the woman\u2019s premature death from the disease. False\u2010positive results do not raise any significant ethical concerns; but they do require a patient to go through an expensive and time\u2010consuming treatment process, and they also cause the patient to experience tension and anxiety that is not warranted. In order to detect cervical cancer in its earliest stages in women, a screening procedure known as a Pap test is often performed. This article describes a technique for improving images using Brightness Preserving Dynamic Fuzzy Histogram Equalization. To individual components and find the right area of interest, the fuzzy c\u2010means approach is applied. The images are segmented using the fuzzy c\u2010means method to find the right area of interest. The feature selection algorithm is the ACO algorithm. Following that, categorization is carried out utilizing the CNN, MLP, and ANN algorithms.<\/jats:p>","DOI":"10.1155\/2023\/1742891","type":"journal-article","created":{"date-parts":[[2023,2,22]],"date-time":"2023-02-22T01:05:09Z","timestamp":1677027909000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":66,"title":["[Retracted] Ant Colony Optimization\u2010Enabled CNN Deep Learning Technique for Accurate Detection of Cervical Cancer"],"prefix":"10.1155","volume":"2023","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9812-2337","authenticated-orcid":false,"given":"R.","family":"Kavitha","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1928-996X","authenticated-orcid":false,"given":"D. 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