Open Access   Article Go Back

Regression Technique to Predict Stages of Basal Cell Carcinoma

Sanjana M1 , V. Hanuman Kumar2

Section:Survey Paper, Product Type: Journal Paper
Volume-7 , Issue-4 , Page no. 1006-1010, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i4.10061010

Online published on Apr 30, 2019

Copyright © Sanjana M, V. Hanuman Kumar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Sanjana M, V. Hanuman Kumar, “Regression Technique to Predict Stages of Basal Cell Carcinoma,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.1006-1010, 2019.

MLA Style Citation: Sanjana M, V. Hanuman Kumar "Regression Technique to Predict Stages of Basal Cell Carcinoma." International Journal of Computer Sciences and Engineering 7.4 (2019): 1006-1010.

APA Style Citation: Sanjana M, V. Hanuman Kumar, (2019). Regression Technique to Predict Stages of Basal Cell Carcinoma. International Journal of Computer Sciences and Engineering, 7(4), 1006-1010.

BibTex Style Citation:
@article{M_2019,
author = {Sanjana M, V. Hanuman Kumar},
title = {Regression Technique to Predict Stages of Basal Cell Carcinoma},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {7},
Issue = {4},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {1006-1010},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4157},
doi = {https://doi.org/10.26438/ijcse/v7i4.10061010}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i4.10061010}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4157
TI - Regression Technique to Predict Stages of Basal Cell Carcinoma
T2 - International Journal of Computer Sciences and Engineering
AU - Sanjana M, V. Hanuman Kumar
PY - 2019
DA - 2019/04/30
PB - IJCSE, Indore, INDIA
SP - 1006-1010
IS - 4
VL - 7
SN - 2347-2693
ER -

VIEWS PDF XML
421 273 downloads 162 downloads
  
  
           

Abstract

With the advent of Artificial Intelligence and Machine learning, healthcare is not limited to mere scans and tests, but also caters to doctors helping them diagnose the medical disorder at hand. One such field of healthcare is diagnosis of skin cancer which is also called as Basal cell carcinoma. This is often caused due to deficiency of a skin pigment called melanin, which may deplete due to harsh environmental conditions. This paper concentrates on a machine learning algorithm to detect skin cancer. The accuracy is found to be 90%.

Key-Words / Index Term

Skin cancer, melanoma, melanin, benign, machine learning

References

[1] Detection skin cancer using SVM and snake model. Bumrungkun, P., Chamnongthai, K., & Patchoo, W. 2018 International Workshop on Advanced Image Technology
[2] Deep Convolution Pixel-wise Labeling for skin lesion Image Segmentation ,Ali Youssef ;Domenico D. Bloisi ;Mario Muscio ; Andrea Pennisi ; Daniele Nardi ; Antonio Facchiano IEEE International Symposium on Medical Measurements and Applications (MeMeA) Year: 2018
[3] A SVM based diagnosis of melanoma using only useful image features, Suleiman Mustafa; Akio Kimura , International Workshop on Advanced Image Technology (IWAIT) Year-2018
[4] Early Detection of Melanoma Skin Cancer Using Classifiers, VS. Sabeera, P. Vamsi Krishna PG Scholar, Dept. of ECE, R. K. College of Engineering, Vijayawada, Andhra Pradesh Assistant Professor, Dept. of ECE, R.K. College of Engineering, Vijayawada, Andhra Pradesh, Year-2016
[5] Skin Cancer Detection and classification Pratik Dubal, Sankirtan Bhatt, Chaitanya Joglekar, Dr. Sonali Patil, and Department of Information Technology K. J. Somaiya College of Engineering Vidyavihar, Year-2017
[6] Skin Cancer Detection using Artificial Neural Network,
Ekta Singhal M.Tech II Year, Dept of Computer Science Engineering, MUST – FET, Lakshmangarh, India Shamik Tiwari, Assistant Professor, Dept of Computer Science Engineering, MUST – FET, Lakshmangarh, India, Year-2015
[7] Detection of Skin Cancer Using Image Processing Techniques, Chandrahasa M, Varun Vadigeri and Dixit Salecha, Computer Science and Engineering, The National Institute of Engineering, Year-2016
[8] Image Processing for Skin Cancer Features Extraction Md.Amran Hossen Bhuiyan, Ibrahim Azad, Md.Kamal Uddin, Department of Computer Science & Telecommunication Engineering, Noakhali Science & Technology University, Bangladesh, International Journal of Scientific & Engineering Research Volume 4, Issue 2, February-2013