Dengue Fever: State-of-the-Art Symptoms and Diagnosis
Tanmay Kasbe1 , Ravi Singh Pippal2
Section:Research Paper, Product Type: Journal Paper
Volume-4 ,
Issue-6 , Page no. 26-30, Jun-2016
Online published on Jul 01, 2016
Copyright © Tanmay Kasbe, Ravi Singh Pippal . 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.
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IEEE Style Citation: Tanmay Kasbe, Ravi Singh Pippal, “Dengue Fever: State-of-the-Art Symptoms and Diagnosis,” International Journal of Computer Sciences and Engineering, Vol.4, Issue.6, pp.26-30, 2016.
MLA Style Citation: Tanmay Kasbe, Ravi Singh Pippal "Dengue Fever: State-of-the-Art Symptoms and Diagnosis." International Journal of Computer Sciences and Engineering 4.6 (2016): 26-30.
APA Style Citation: Tanmay Kasbe, Ravi Singh Pippal, (2016). Dengue Fever: State-of-the-Art Symptoms and Diagnosis. International Journal of Computer Sciences and Engineering, 4(6), 26-30.
BibTex Style Citation:
@article{Kasbe_2016,
author = {Tanmay Kasbe, Ravi Singh Pippal},
title = {Dengue Fever: State-of-the-Art Symptoms and Diagnosis},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2016},
volume = {4},
Issue = {6},
month = {6},
year = {2016},
issn = {2347-2693},
pages = {26-30},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=961},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=961
TI - Dengue Fever: State-of-the-Art Symptoms and Diagnosis
T2 - International Journal of Computer Sciences and Engineering
AU - Tanmay Kasbe, Ravi Singh Pippal
PY - 2016
DA - 2016/07/01
PB - IJCSE, Indore, INDIA
SP - 26-30
IS - 6
VL - 4
SN - 2347-2693
ER -
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Abstract
Fever is the most normal disease in any age group, but it becomes a deadly disease if it has dengue symptoms. Identifying dengue symptoms at an early stage is very difficult because this kind of symptoms is very common in all types of fevers. When fever continues after 3-4 days the symptoms of dengue shown in patients. So far there is no vaccine (According to WHO (World Health Organization) Report in April 2015 First Dengue fever vaccine introduced. We have mention about in this paper) or particular medicine available in market to prevent from the dengue. In today era around 40% population of the world is at risk of dengue fever. Since 1950s, this disease cause several death on globe and unfortunately there is no proper preventive method developed yet. From the long period of time some senior doctors working on categorized dengue fever because symptoms of dengue fever are different for different patients. In this paper we have to provide all cause, symptoms & diagnosis methods.
Key-Words / Index Term
Dengue Fever, Symptoms , Deadly disease,Dignosis System
References
[1] Varinder Pabbi, “Fuzzy Expert System for Medical Diagnosis”, International Journal of Scientific and Research Publications, Volume 5, Issue 01, pp. 1-7, 2015.
[2] Dayaraj Cecilia,” Current status of dengue and chikangunia in India”, WHO South-East Asia Journal of Public Health, ISSN: 2224-3151, pp.23-27, January-March 2013.
[3] Sharanjit Singh, Amardeep Singh, Samson, Malkeet Singh, “Recommended System for Detection of Dengue Using Fuzzy Logic”, International Journal of Computer Engineering & Technology (IJCET), Volume 7, Issue 2, pp. 44–52, March-April 2016.
[4] Tajul Rosli Bin Razak, Muhammad Hermi Ramli, Rosmawati Abd. Wahab, “Dengue Notification System using Fuzzy Logic”, International Conference on Computer, Control, Informatics and Its Applications, pp. 231-235, November 2013.
[5] Rao. V, Naresh. M, “A New Intelligence-Based Approach for Computer-Aided Diagnosis of Dengue Fever,” IEEE Transactions on Information Technology in Biomedicine, Volume 16, Issue 1, pp. 112-118, 2012.
[6] Nivedita Gupta, Sakshi Srivastava, Amita Jain, Umesh C. Chaturvedi, “Dengue in India”, Indian Council of Medical Research, New Delhi & Department of Microbiology KG Medical University, Lucknow, India, pp. 373-390, September 2012.
[7] Raul Beltran Ramírez, Rocio Maciel Arellano, Carlos Gonzalez Sandoval, Adauto Casas Flores, “An Expert System Oriented towards the Detection of Influenza and Dengue Developed on Mobile Platforms”, Journal of Software Engineering and Applications, Volume 8, pp. 295-301, June 2015.
[8] Kunjal Bharatkumar Mankad, “Design of Genetic-Fuzzy Based Diagnostic System to identify Chikangunia”, International Research Journal of Engineering and Technology (IRJET), Volume 02, Issue 04, pp.153-161, July 2015.
[9] Anil Pardeshi, Ratnendra Shinde, Abhijeet Jagtap, Ravindra Kembhavi, Mayur Giri, Snehal Kavathekar, “Retrospective Cross-sectional Study of Dengue Cases in IPD with Reference to Treatment- Monitoring & Outcome in KEM Hospital, Mumbai”, American Journal of Epidemiology and Infectious Disease, Volume 2, Issue 4, pp. 97-100, September 2014.
[10] Manish Rana, R. R. Sedamkar, “Design of Expert System for Medical Diagnosis Using Fuzzy Logic”, International Journal of Scientific & Engineering Research, Volume 4, Issue 6, pp.2914-2921, June 2013.
[11] S. Govinda Rao, M. Eswara Rao, D. Siva Prasad, “Fever Diagnosis Rule-Based Expert Systems”, International Journal of Engineering Research & Technology (IJERT), Volume 2, Issue 8, pp. 551-561, August 2013.
[12] Putu Manik Prihatini, Ketut Gede Darma Putra, “Fuzzy Knowledge-based System with Uncertainty for Tropical Infectious Disease Diagnosis”, IJCSI International Journal of Computer Science Issues, Volume 9, Issue 4, pp. 157-163, July 2012.
[13] Oguntimilehin A, Adetunmbi A.O, Olatunji K.A, “A Machine Learning Based Clinical Decision Support System for Diagnosis and Treatment of Typhoid Fever”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 4, Issue 6, pp. 961-969, June 2014.
[14] Baig, Faran, Khan, Saleem, Noor, Yasir Noor, M. Imran, “Design model of fuzzy logic medical diagnosis control system” International Journal on Computer Science and Engineering (IJCSE), Volume 3, Issue 5, May 2011.
[15] Priyanka Sharma, DBV Singh, Manoj Kumar Bandil, Nidhi Mishra, “Decision Support System for Malaria and Dengue Disease Diagnosis (DSSMD)”, International Journal of Information and Computation Technology, Volume 3, Issue 7, pp. 633-640, 2013.
[16] Kamran Shaukat, Nayyer Masood, Sundas Mehreen, Ulya Azmeen, “Dengue Fever Prediction: A Data Mining Problem”, Data Mining in Genomics & Proteomics, Volume 6, Issue 3, pp. 1-5, 2015.
[17] Muhammad Arif Nadeem Saqib, Ibrar Rafique, Saira Bashir, Arsalan Ahmad Salam, “A retrospective analysis of dengue fever case management and frequency of co-morbidities associated with deaths”, BMC Research, Volume 4, Issue 6, pp. 1-5, March 2014.
[18] Tarig Faisal, Mohd Nasir Taib, Fatimah Ibrahim, “Adaptive Neuro-Fuzzy Inference System for diagnosis risk in dengue patients”, Expert System with Applications, ELSEVIER, Volume 39, Issue 4, pp. 4483-4495, March 2012.
[19] M. V. Jagannatha Reddy and B. Kavitha, “Expert System to Predict the Type of Fever Using Data Mining Techniques on Medical Database”, International Journal of Computer Science and Engineering, Volume 03, Issue 09, pp. 165-171, September 2015.
[20] M. Palaniyandi, “The environmental aspects of dengue and chikungunya outbreaks in India: GIS for epidemic control”, International Journal of Mosquito Research, Volume 1, Issue 2, June 2014.