دورية أكاديمية
Analysis of Skin Cancer and Patient Healthcare Using Data Mining Techniques.
| العنوان: | Analysis of Skin Cancer and Patient Healthcare Using Data Mining Techniques. |
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| المؤلفون: | Arivazhagan N; Department of Computational Intelligence, SRM Institute of Science and Technology, SRM Nagar, Kattankulathur 603203, India., Mukunthan MA; School of Computing, Department of Computer Science and Engineering, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, India., Sundaranarayana D; Department of Computer Science and Engineering, Veltech Rangarajan Dr. Sagunthala R &D Institute of Science and Technology, Avadi, Chennai, India., Shankar A; Department of ECE, Manakula Vinayagar Institute of Technology, Puducherry, India., Vinoth Kumar S; School of Computing, Department of Computer Science and Engineering, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, India., Kesavan R; Institute of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, India., Chandrasekaran S; Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai, India., Shyamala Devi M; School of Computing, Department of Computer Science and Engineering, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, India., Maithili K; School of Computing, Department of Computer Science and Engineering, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, India., Barakkath Nisha U; Department of Information Technology, Sri Krishna College of Engineering and Technology, Coimbatore, India., Abebe TG; School of Computing, Department of Computer Science and Engineering, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Avadi, Chennai, India.; Department of Chemical Engineering, College of Biological and Chemical Engineering, Addis Ababa, Ethiopia. |
| المصدر: | Computational intelligence and neuroscience [Comput Intell Neurosci] 2022 Sep 26; Vol. 2022, pp. 2250275. Date of Electronic Publication: 2022 Sep 26 (Print Publication: 2022). |
| نوع المنشور: | Journal Article; Review |
| اللغة: | English |
| بيانات الدورية: | Publisher: Hindawi Pub. Corp Country of Publication: United States NLM ID: 101279357 Publication Model: eCollection Cited Medium: Internet ISSN: 1687-5273 (Electronic) NLM ISO Abbreviation: Comput Intell Neurosci Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: New York, NY : Hindawi Pub. Corp. |
| مواضيع طبية MeSH: | Dermoscopy*/methods , Skin Neoplasms*/diagnosis , Skin Neoplasms*/pathology, Algorithms ; Data Mining ; Delivery of Health Care ; Female ; Humans ; Male |
| مستخلص: | Skin cancer is the uncontrolled growth of irregular cancer cells in the human-skin's outer layer. Skin cells commonly grow in an uneven pattern on exposed skin surfaces. The majority of melanomas, aside from this variety, form in areas that are rarely exposed to sunlight. Harmful sunlight, which results in a mutation in the DNA and irreparable DNA damage, is the primary cause of skin cancer. This demonstrates a close connection between skin cancer and molecular biology and genetics. Males and females both experience the same incidence rate. Avoiding revelation to ultraviolet (UV) emissions can lower the risk rate. This needed to be known about in order to be prevented from happening. To identify skin cancer, an improved image analysis technique was put forth in this work. The skin alterations are routinely monitored by this proposed skin cancer categorization approach. Therefore, early detection of suspicious skin changes can aid in the early discovery of skin cancer, increasing the likelihood of a favourable outcome. Due to the blessing of diagnostic technology and recent advancements in cancer treatment, the survival rate of patients with skin cancer has grown. The strategy for detecting skin cancer using image processing technologies is presented in this paper. The system receives the image of the skin lesion as an input and analyses it using cutting-edge image processing methods to determine whether skin cancer is present. The Lesion Image Analysis Tools use texture, size, and shape assessment for image segmentation and feature phases to check for various cancer criteria including asymmetries, borders, pigment, and diameter. The image is classified as Normal skin and a lesion caused by skin cancer using the derived feature parameters. Competing Interests: The authors declare that they have no conflicts of interest. (Copyright © 2022 N. Arivazhagan et al.) |
| References: | Artif Intell Med. 2020 Jan;102:101779. (PMID: 31980109) Biomed Res Int. 2022 Apr 16;2022:7799812. (PMID: 35480141) Diagnostics (Basel). 2021 Apr 29;11(5):. (PMID: 33947117) IEEE Trans Med Imaging. 2020 Jul;39(7):2482-2493. (PMID: 32070946) Biomed Pharmacother. 2021 Sep;141:111875. (PMID: 34229250) Med Image Anal. 2017 Jan;35:18-31. (PMID: 27310171) Comput Biol Med. 2020 Dec;127:104065. (PMID: 33246265) Sensors (Basel). 2018 Aug 04;18(8):. (PMID: 30081540) Comput Methods Programs Biomed. 2016 Jul;131:127-41. (PMID: 27265054) Molecules. 2021 Feb 03;26(4):. (PMID: 33546290) J Healthc Eng. 2022 Feb 14;2022:2761847. (PMID: 35198132) Comput Med Imaging Graph. 2011 Mar;35(2):105-15. (PMID: 20832992) J Adv Res. 2021 Jun 16;36:223-247. (PMID: 35127174) J Clin Med. 2022 Jan 14;11(2):. (PMID: 35054123) J Healthc Eng. 2022 Apr 18;2022:1709842. (PMID: 35480147) Sci Rep. 2022 Mar 14;12(1):4329. (PMID: 35288579) |
| تواريخ الأحداث: | Date Created: 20221006 Date Completed: 20221007 Latest Revision: 20221011 |
| رمز التحديث: | 20231215 |
| مُعرف محوري في PubMed: | PMC9529455 |
| DOI: | 10.1155/2022/2250275 |
| PMID: | 36199959 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1687-5273 |
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| DOI: | 10.1155/2022/2250275 |