CFP last date
20 May 2024
Reseach Article

User Awareness System to Diagnose Dermatological Diseases

by Vithushiyan Pathivarathan, Naveenan Thavabalasingham, Kasvithan Philipreman, Sinmayan Gunasekaran, Sanjeevi Chandrasiri, Thilini Weerasooriya
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 36
Year of Publication: 2020
Authors: Vithushiyan Pathivarathan, Naveenan Thavabalasingham, Kasvithan Philipreman, Sinmayan Gunasekaran, Sanjeevi Chandrasiri, Thilini Weerasooriya
10.5120/ijca2020920925

Vithushiyan Pathivarathan, Naveenan Thavabalasingham, Kasvithan Philipreman, Sinmayan Gunasekaran, Sanjeevi Chandrasiri, Thilini Weerasooriya . User Awareness System to Diagnose Dermatological Diseases. International Journal of Computer Applications. 175, 36 ( Dec 2020), 30-35. DOI=10.5120/ijca2020920925

@article{ 10.5120/ijca2020920925,
author = { Vithushiyan Pathivarathan, Naveenan Thavabalasingham, Kasvithan Philipreman, Sinmayan Gunasekaran, Sanjeevi Chandrasiri, Thilini Weerasooriya },
title = { User Awareness System to Diagnose Dermatological Diseases },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2020 },
volume = { 175 },
number = { 36 },
month = { Dec },
year = { 2020 },
issn = { 0975-8887 },
pages = { 30-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number36/31686-2020920925/ },
doi = { 10.5120/ijca2020920925 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:40:26.972010+05:30
%A Vithushiyan Pathivarathan
%A Naveenan Thavabalasingham
%A Kasvithan Philipreman
%A Sinmayan Gunasekaran
%A Sanjeevi Chandrasiri
%A Thilini Weerasooriya
%T User Awareness System to Diagnose Dermatological Diseases
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 36
%P 30-35
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Nowadays, humans' health is deteriorating by dermatological diseases, and the spreading rate is high. Most people are not aware of skin diseases. As they do not realize these diseases' seriousness, they try to treat with some remedies by themselves, even without knowing what the actual disease is. Nevertheless, it is not a suitable way to cure the disease, leading to future complications. So still the dermatological diseases remain as one of the main categories of common health issues. A few people prefer to use computerized systems to evaluate the disease conditions these days. Moreover, it is essential to know about the diseases to manage that condition and prevent escalation. Therefore, the proposed system is implemented to give users some knowledge about dermatological diseases as much as possible. The users can get awareness and predict skin diseases and complications from the data mining technique. The user can identify the stage of the dermatological disease by applying the classification algorithm. Furthermore, this system will also scrap web pages related to that disease from known or system verified websites. The content analysis is based on the machine learning process, especially using Neural Language Processing. Hence, the system will undeniably be useful to the users to summarize skin diseases and get concerns from a dermatologist.

References
  1. Ulf Mader, Niko Quiskamp, Soren Wildenhain, Thomas Schmidts, Peter Mayser, Frank Runkel and Martin Fiebich, , Image-Processing Scheme to Detect Superficial Fungal Infections of the Skin, Germany: Hindawi, 2015
  2. Beth Snyder Bulik, ‘Almirall 'Shared Skin' dermatology disease awareness campaign gets employees involved’, Jun 13, 2016 [online] Available: https://www.fiercepharma.com/marketing/almirall-shared-skin-dermatology-disease-awareness-campaign-gets-employees-involved
  3. I. Rahat Yasir,,* Md. Ashiqur Rahman, and Nova Ahmed, Electronic and Computer Engineering Department, North South University, Dhaka, Bangladesh.” Dermatological Disease Detection using Image Processing and Artificial Neural Network”- 8th International Conference on Electrical and Computer Engineering 20-22 December, 2014, Dhaka, Bangladesh
  4. Abderrahim Bourouisa ,Ali Zerdazia , Mohammed Fehamb , Abdelhamid Bouchachiac* “M-Health: Skin Disease Analysis System using Smart phone’s camera”-The 8th International Symposium on Intelligent Systems Techniques for Ad hoc and Wireless Sensor Networks (IST-AWSN).
  5. Abderrahim Bourouis, Mohamed Feham,Abdelhamid Bouchachia. Ubiquitous Mobile Health Monitoring System for Elderly (UMHMSE). International Journal of Computer Science & Information Technology ; June 2011 ,Vol 3, No 3.
  6. Al-Taee M.A , Jaradat N.A , Ali, D.M.A. Mobile phone- based health data acquisition system using Bluetooth technology .Applied Electrical Engineering and Computing Technologies (AEECT); 2011 ,p.1-6.
  7. Qing Pan, Pan Yang, Rui Zhang, Chengyu Lin, Shijin Gong, Li Li, Jing Yan, Gangmin Ning . A mobile health system design for home and community use, Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference ;2012 , p. 116 - 119 .
  8. Asada H, Shaltis P, Reisner A, Rhee S, Hutchinson R. Mobile monitoring with wearable photoplethysmograhic biosensors. IEEE Eng Med Biology Mag ;May-June 2003,p. 28 - 40 .
  9. Ross P. Managing care through air. IEEE Spectrum; Dec 2004, p.26- 31.
  10. Anal Kumar MittraandDr. Ranjan Parekh - Automated Detection of Skin Diseases Using Texture Features.
  11. Fitzpatrick, T.B., Rhodes, A.J., Sober, A., Mihm, M. (1988), Primary malignant melanoma of the skin: The call for action to identify persons at risk, to discover precursor lesion, to detect early melanoma. Pigm Cell Res 9(1): 110-7
  12. Granot, Y., Ivorra, A., Rubinsky, B. (2008), A New Concept for Medical Imaging Centered on Cellular Phone Technology PLoS ONE 3(4): e2075. doi:10.1371/journal.pone.0002075
  13. Roya Hassanian-esfahani, Mohammad-javad Kargar, " A Survey on Web News Retrieval and Mining", 2008 9th International Conference on Computer-Aided Industrial Design and Conceptual Design.
  14. Muhammad Qasim Khan,Ayyaz Hussain,Saeed Ur Rehman,Umair Khan,"Classification of Melanoma and Nevus in Digital Images for Diagnosis of Skin Cancer",Department of Computer Science and Software Engineering, International Islamic University, Islamabad 44000, Pakistan
  15. Han J, Kamber M. Data mining : concepts and techniques. 3rd ed. Burlington, MA: Elsevier; 2011.
  16. Güvenir HA, Demiröz G, Ilter N. Learning differential diagnosis of erythemato-squamous diseases using voting feature intervals. Artificial Intelligence in Medicine. 1998;13(3):147–65.
  17. Danjuma K, Osofisan AO. Evaluation of Predictive Data Mining Algorithms in Erythemato-Squamous Disease Diagnosis. International Journal of Computer Science Issues. 2014;11(6):85–94.
  18. Damilola A. Okuboyejo, Oludayo O. Olugbara, and Solomon A. Odunaike (2013) - Automating Skin Disease Diagnosis Using Image Classification-Proceedings of the World Congress on Engineering and Computer Science 2013, Volume II, San Francisco, USA.
  19. S.Saha,"towardsdatascience,"[Online].Available:https://towardsdatascience.com/a-comprehensive-guide-toconvolutional-neural-networks-the-eli5-way-3bd2b1164a53. [Accessed 15 December 2018].
  20. F. Chollet, “Building powerful image classification models using very littledata,”2016.[Online].Available: https://blog.keras.io/buildingpowerful-image-classificationmodels-using-very-little-data.html. [Accessed: 05-Mar-2019]
  21. S. Paranavitana, Inscriptions of Ceylon, Department of Archaeology, Colombo, Sri lanka, 1970.
  22. Esteban Borges, “Exploring Google Hacking Techniques”, [online], Available: https://securitytrails.com/blog/google-hacking-techniques
  23. Young-Jun Lee, Chan-Yong Park, Ho-Jin Choi, “Word-level Emotion embedding based on Semi-Supervised Learning for Emotional Classification in Dialogue”, Korea Electric Power Corporation, Grant number: R18XA05
  24. Chunyu Xia, Tieke He, Wenlong Li, Zemin Qin, Zhipeng Zou, “Similarity Analysis of Law Documents Based on Word2vec”, IEEE 19th International Conference on Software Quality, Reliability and Security Companion (QRS-C), 2019
  25. Satuluri Vanaja, Meena Belwal, “Aspect-Level Sentiment Analysis on E-Commerce Data”, Proceedings of the International Conference on Inventive Research in Computing Applications (ICIRCA), 2018.
  26. Gennady Osipov, Ivan Smirnov, Ilya Tikhomirov, Olga Vybornova, “Technologies for Semantic Analysis of Scientific Publications”, Institute for Systems Analysis Russian Academy of Sciences, 2012
Index Terms

Computer Science
Information Sciences

Keywords

Dermatological diseases Image processing Data mining Web scraping Natural Language Processing