Lung Cancer Classification and Prediction Using Machine Learning and Image Processing.
Lung cancer is a potentially lethal illness. Cancer detection continues to be a challenge for medical professionals. The true cause of cancer and its complete treatment have still not been discovered. Cancer that is caught early enough can be treated. Image processing methods such as noise reduction...
| Publicado en: | BioMed Research International pp. 1 - 9 |
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| Autores principales: | , , , , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
8/22/2022
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| 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=158648032&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 158648032 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 8/22/2022 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 158648032 158648032 158648032 10.1155/2022/1755460 158648032 ppf: 1 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Lung Cancer Classification and Prediction Using Machine Learning and Image Processing. aug: au: Nageswaran, Sharmila Arunkumar, G. Bisht, Anil Kumar Mewada, Shivlal Kumar, J. N. V. R. Swarup Jawarneh, Malik Asenso, Evans affil: Department of Sensor and Biomedical Technology, School of Electronics Engineering, Vellore Institute of Technology, Tamil Nadu, India sug: subj: Lung Neoplasms Classification Lung Neoplasms Radiography Prediction Models Machine Learning Image Processing, Computer Assisted Tomography, X-Ray Computed Sensitivity and Specificity Human Experimental Studies Radiographic Image Interpretation, Computer-Assisted Cancer Patients Neoplasm Staging Descriptive Statistics ab: Lung cancer is a potentially lethal illness. Cancer detection continues to be a challenge for medical professionals. The true cause of cancer and its complete treatment have still not been discovered. Cancer that is caught early enough can be treated. Image processing methods such as noise reduction, feature extraction, identification of damaged regions, and maybe a comparison with data on the medical history of lung cancer are used to locate portions of the lung that have been impacted by cancer. This research shows an accurate classification and prediction of lung cancer using technology that is enabled by machine learning and image processing. To begin, photos need to be gathered. In the experimental investigation, 83 CT scans from 70 distinct patients were utilized as the dataset. The geometric mean filter is used during picture preprocessing. As a consequence, image quality is enhanced. The K -means technique is then used to segment the images. The part of the image may be found using this segmentation. Then, classification methods using machine learning are used. For the classification, ANN, KNN, and RF are some of the machine learning techniques that were used. It is found that the ANN model is producing more accurate results for predicting lung cancer. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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