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International Journal of Information Technology and Computer Science(IJITCS)

ISSN: 2074-9007 (Print), ISSN: 2074-9015 (Online)

Published By: MECS Press

IJITCS Vol.9, No.10, Oct. 2017

Fuzzy Based Multi-Fever Symptom Classifier Diagnosis Model

Full Text (PDF, 567KB), PP.13-28


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Author(s)

Ighoyota Ben Ajenaghughrure, P. Sujatha, Maureen I. Akazue

Index Terms

Fuzzy classifier;fever diagnosis;multi fever;expert fever diagnosis

Abstract

Fever has different causes and types, but with similar symptoms. Therefore, making fever diagnosis with human physiological symptoms more complicated. This research project delves into the design of a web based expert multi-fever diagnosis system using a novel fuzzy symptom classifier with human self-observed physiological symptoms. Considering malaria, Lassa, dengue, typhoid and yellow fever. The fuzzy-symptom classifier has two stages. Fist stage is fever type confirmation  using common fever symptoms, leading to five major fuzzy rules and the second phase is determining the level of infection (severe or mild) of the confirmed type of fever using unique fever symptoms. Furthermore, Case studies during the system implementation yielded data collected from 50 patients of having different types of fever. The analysis clearly shows the effectiveness and accuracy in the system performance through false result elimination. In addition, acceptability of the system was investigated through structured questionnaire administered to same 50 patients. This result clearly indicates that the system is well accepted, by users and considered fairly easy to use, time and cost saving.

Cite This Paper

Ighoyota Ben Ajenaghughrure, P. Sujatha, Maureen I. Akazue, "Fuzzy Based Multi-Fever Symptom Classifier Diagnosis Model", International Journal of Information Technology and Computer Science(IJITCS), Vol.9, No.10, pp.13-28, 2017. DOI: 10.5815/ijitcs.2017.10.02

Reference

[1]James M Heilman, Jacob De Wolff, Graham M Beards, Brian J Basden, Dengue fever: a Wikipedia clinical review , Open Medicine;vol8 issue4 page105, 2014.

[2]ichirokuran, dengue hemorrhagic fever with special emphasis on immunopathogenesis, journal of comaparative immunology and microbiologyand infectious disease, 2007, doi/10.1016/j.cimid.2007.05.010

[3]RiazA,AmirRiazDengue fever: Prevention most recommended, theHealth Vol 2, Issue 2, pp33-34, 2011

[4]Fever: Its Biology, Evolution, and Function. Princeton University Press.. p. 57. ISBN 9781400869831. 2015

[5]Garmel, Fever in adultsGus M, An   introduction to clinical emergency medicine (2nd ed.). Cambridge: Cambridge University Press. p. 375. ISBN 0521747767.

[6]Section on Clinical Pharmacology and, Therapeutics; Committee on, Drugs; Sullivan, JE; Farrar, HC "Fever and antipyretic use in children.".Pediatrics127 (3): 580–7. 2011.

[7]Garmel, edited by S.V. Mahadevan, Gus M. An introduction to clinical emergency medicine (2nd ed.). Cambridge: Cambridge University Press. p. 5.  2012..

[8]Richardson, M; Purssell, E  "Who's afraid of fever?". Archives of Disease in Childhood 100 (9): 818–20. September 2015.

[9]Garmel, edited by S.V. Mahadevan, Gus M. An introduction to clinical emergency medicine (2nd ed.). Cambridge: Cambridge University Press. p. 401. 2012.

[10]Kiekkas, P; Aretha, D; Bakalis, N; Karpouhtsi, I; Marneras, C; Baltopoulos, GI "Fever effects and treatment in critical care: literature review.". Australian Critical Care 26 (3): 130–5. August 2013.

[11]Niven, Daniel J.; Gaudet, Jonathan E.; Laupland, Kevin B.; Mrklas, Kelly J.; Roberts, Derek J.; Stelfox, Henry Thomas "Accuracy of Peripheral Thermometers for Estimating Temperature". Annals of Internal Medicine 163 (10): 768. 17 November 2015.

[12]Barone JE "Fever: Fact and fiction".  J Trauma  Vol. 67 Issue2,  PP406–409, (August 2009).. 

[13]jyh-sing roger jang, chuen-tsai.sun, and eijl mizutani, Neurofuzzy and soft computing: A computational approach to learning and machine intelligence, Eastern Economy Edition, 17 November 2015.

[14]Oguntimilehin A,  Adetunmbi A.O. and  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.

[15]Tarig Faisal, Mohd Nasir Taib, Fatimah Ibrahim, Adaptive Neuro-Fuzzy Inference System for diagnosis risk in dengue patients (PDF) Accessed 21/03/2016

[16]Sharifah Hanis, and BT Syed Ahmad, an expert system to track dengue fever A thesis submitted in fulfillment of the requirement for the award of the degree of Bachelor of Computer Science (PDF) Accessed 21/03/2016

[17]O.W. Samuel, M.O. Omisore, B.A. Ojokoh, A web based decision support system driven by fuzzy logic for the diagnosis of typhoid fever, Expert Systems with Applications Journal, Expert Systems with Applications Vol.40, PP 4164–4171, 2013.

[18]X.Y. Djam1, G. M. Wajiga, Y. H. Kimbi and N.V. Blamah,A Fuzzy Expert System for the Management of Malaria, International Journal of Pure and Applied Sciences and Technology, Vol.5, Issue2, pp84-108, 2011.

[19]Priynka Sharma, DBV Singh, Manoj Kumar Bandil and Nidhi Mishra, Decision Support System for Malaria and Dengue Disease Diagnosis (DSSMD), International Journal of Information and Computation Technology.Volume 3, Number 7, pp. 633-640, 2013.

[20]Adetunmbi A.O, Oguntimilehin A, Falaki S.O., web-based medical assistant system for malaria diagnosis and therapy  GESJ: Computer Science and Telecommunications, Vol. 1 No.33, 2012, PP42-53, June 2014 

[21]sunday tunmibi, oriyomi adeniji,  ayooluwa aregbesola, and ayodeji dasylva, a rule based expert system for diagnosis of fever,  International Journal of Advanced Research, Volume 1, Issue 7,  2013,pp343

[22]Jimoh R.G., Awotunde J.B., Babatunde A. O., Ameen, A. O & Fatia O.W, Simulation Of Medical Diagnosis System For Malaria Using Fuzzy Logic , Computing, Information Systems, Development Informatics & Allied Research Journal Vol. 5 No. 2.,  Pp59-68, June 2014

[23]Ojeme Blessing Onuwa, Fuzzy Expert System For Malaria Diagnosis, Oriental Journal Of Computer Science & Technology, Vol. 7, No. (2),  , pp 273-284, June 2014

[24]Normile D. Surprising new dengue virus throws a spanner in disease control efforts. Tropical medicine Science, Vol342, issue 6157, page415, 2013 

[25]Sue E. Huether, Pathophysiology: The Biologic Basis for Disease in Adults and Children (7 ed.). Elsevier Health Sciences. p. 498, 2014.. 

[26]Kalyani Baghel, Neeraj Mehta, A Web Based Fuzzy Expert System for Human Disease Diagnosis, International Journal Of Engineering And Computer Science Volume 4 Issue 9, Pp. 14248-14253, Sep 2015

[27]Nidhi mishra,  and  P. Jha, A review on the applications of fuzzy expert system for disease diagnosis, international journal of advanced research in engineering and applied sciences vol. 3, no. 12 pp 28 -43, December 2014.

[28]Asogbon MG, Samuel OW, Omisore MO and Awonusi O, Enhanced Neuro-Fuzzy System Based on Genetic Algorithm for Medical Diagnosis, Journal of Medical Diagnostic Method Volume 5, Issue 1-1000205. doi: 10.4172/2168-9784.1000205

[29]S. Govinda Rao M. Eswara Rao D. Siva Prasad Diagnosis Rule-Based Expert Systems  International Journal of Engineering Research & Technology (IJERT) Vol. 2 Issue 8, pp551-561, August – 2013