Ant Colony Optimization-Enabled CNN Deep Learning Technique for Accurate Detection of Cervical Cancer.
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 ma...
| Publicado en: | BioMed Research International pp. 1 - 10 |
|---|---|
| Autores principales: | , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
2/21/2023
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=162008239&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 162008239 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 2/21/2023 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 162008239 162008239 162008239 10.1155/2023/1742891 162008239 ppf: 1 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Ant Colony Optimization-Enabled CNN Deep Learning Technique for Accurate Detection of Cervical Cancer. aug: au: Kavitha, R. Jothi, D. Kiruba Saravanan, K. Swain, Mahendra Pratap Gonzáles, José Luis Arias Bhardwaj, Rakhi Joshi Adomako, Elijah affil: Sri Ram Nallamani Yadava Arts and Science College, Manonmaniam Sundaranar University, Tirunelveli, India sug: subj: Cervix Neoplasms Diagnosis Deep Learning Neural Networks (Computer) Diagnostic Errors Prevention and Control Human Female Cancer Patients False Positive Results Stress, Psychological Anxiety Algorithms Female ab: 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-negative 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's premature death from the disease. False-positive results do not raise any significant ethical concerns; but they do require a patient to go through an expensive and time-consuming 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-means approach is applied. The images are segmented using the fuzzy c-means 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. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|