The week's pick
Random Articles
Reseach Article
Computer Aided Diagnostic Systems for Managing Typhoid Fever: A Review of Diagnosis Techniques
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 126 - Number 6 |
| Year of Publication: 2015 |
| Authors: Oguntimilehin A., Abiola O.B., Olatunji K.A. |
10.5120/ijca2015906071
|
Oguntimilehin A., Abiola O.B., Olatunji K.A. . Computer Aided Diagnostic Systems for Managing Typhoid Fever: A Review of Diagnosis Techniques. International Journal of Computer Applications. 126, 6 ( September 2015), 24-29. DOI=10.5120/ijca2015906071
Abstract
Information Technology (IT) has been of immense benefits in all areas of human endeavours and medicine is not an exceptional case as it has been used in bringing hospitals to homes. A number of computer aided diagnostic systems have been developed to carry out diagnosis, provide therapy or perform both. Most of these systems are desirable due to many factors which include shortages of medical experts, hospitals and medical equipment. There are hundreds of such systems today managing diseases as standalone or web-based or mobile application in which Typhoid Fever is not left out. Typhoid Fever has been identified as one of the major killers and common diseases which kill more than the dreaded Acquired Immune Deficiency Syndrome (AIDS). Though drugs are available for the treatment of Typhoid Fever as against the dreaded (AIDS) but the large number of deaths are as a result of poor or misdiagnosis or no diagnosis at all as a result of shortage of medical expert, hospitals and equipment among others. It is good to use IT in medicine but the practice must be done with care. It was observed in this work that some of the available computer aided diagnostic systems on Typhoid Fever are mere software development exercise without any consultation with medical experts, strong diagnosis background and deployment of computational tools or predictive algorithms. Six basic stages or elements that can make a diagnostic system reliable were suggested in this work for researchers working in the area of developing Computer Aided Diagnostic and Therapy Systems.
References
- Nana Yaw Asabere (2012). mMES: A Mobile Medical Expert System for Health Institutions in Ghana, International Journal of Science and Technology, volume 2 No6. 2012. www.ejournalofsciences.org. Retrieved 07/02/14.
- Adehor A.B. and Burrell P.R. (2008), “An Intelligent Decision Support System for the Prompt Diagnosis of Malaria and Typhoid fever in the Malaria Belt of Africa”, Artificial Intelligence in Theory and Practice II, Pg288-295. www.dl.ifi.org/index.php/AICT/article/. Retrieved 04/04/14.
- Adehor A.B and Burrell P.R. (2008),“ The integrated Management of Healthare Strategies and Differential Diagnosis by Expert System Technology: a single- dimensional approach”, World Academy of Sciences, Engineering and Technology,pp533-538,2008, http://www.waset.org/journa. Retrieved 08/05/13.
- Adetunmbi A.O, Oguntimilehin A. and Falaki S.O (2012), “Web-Based Medical Assistant System for Malaria Diagnosis and Therapy”, GESJ: Computer Science and Telecommunications No1(33), Pg 42-53.
- WHO (2007), “Taking Stock: Health Workers Shortages and the Response to AIDS”,www.who.int /health systems/.../TTR. Retrieved 04/04/14
- Oguntimilehin A., Adetunmbi A.O. and Abiola O.B.(2013), “A Machine Learning Approach to Clinical Diagnosis of Typhoid Fever”, International Journal of Computer and Information Technology(ISSN:2279-0764), Volume 02- issue 04, July 2013. www.ijcit.com. Retrieved 01/02/14.
- Oguntimilehin A , Adetunmbi A. and Olatunji K., A Machine Learning Based Clinical Decision Support System for the Diagnosis and Treatment of Typhoid Fever, International Journal of Advanced Research in Computer Science and Software Engineering. Volume 4, Issue 6, June 2014, Pg 961-969. www.ijarcsse.com
- Oguntimilehin A, Adetunmbi A.O. and Abiola O.B., A Review of Predictive Models on Diagnosis and Treatment of Malaria Fever, International Journal of Computer Science and Mobile Computing,Vol.4 Issue.5, May 2015, pg. 1087-1093. http://www. ijcsmc.com. Retrieved 29/06/2015
- Oguntimilehin A and Ademola E.O, A Framework for Mobile Health Management for Diseases in Nigeria with Benefits and Challenges, International Journal of Computing, Communications and Networking, Vol 3 No 1 April- June, 2014 Pg 19-24, http://www.warse.org
- Samuel Oluwarotimi Williams and Omisore Mumini Olatunji(2013), “Hybrid Intelligent System for the Diagnosis of Typhoid Fever”, Journal of Computer and Information Technology 2:2, pg1-9.
- Sunday Tunmibi, Oriyomi Adeniji, Ayooluwa Aregbesola and Ayodeji Dasylva(2013), “ A Rule Based Expert System for Diagnosis of Fever”, International Journal of Advanced Research, vol1, issue 7, pg 343-348. www.journalijar.com. Retrieved 12/03/14.
- S. Khan, B.N. Harish, G.A. Menezes, N.S. Acharya & S.C. Parija(2012), “ Early Diagnosis of Typhoid Fever by nested PCR for flagellin gene of Salmonella enterica Serotype Typi”, Indian J Med Res 136, November 2012, pp 850-854.
- O.W Samuel, M. Omisore and B.A. Ojokoh (2013), “A Web Based Decision Support System driven by Fuzzy Logic for the diagnosis of typhoid fever”, Expert Systems with Applications 40(2013), pg 4164-417, www.elsevier.com/locate/eswa, Retrieved 21/05/2015.
- Rashid Ansumana et al (2013), “Presumptive Self-diagnosis of Malaria and other febrile illness in Sierra Leone”, Pan African Medical Journal. Availabe online at:http://www.panafrican-med-journal.com
- S.A Fatumo, Emmanuel Adetiba, J.O Onolapo (2013), “Implementation of XpertMaltyph: An Expert System for Medical Diagnosis of the Complication of Malaria and Typhoid “, IOSR Journal of Computer Engineering, vol 8, issue 5, Jan-Feb 2013, Pg 34-40, www.iosrjournals.org.
- Oladipo O, Olayinka C.T and Popoola O.L, “Mobile Compactable Expert System for the Treatment of Typhoid Fever in Developing Countries”, International Journal of Computer Applications, Vol5-No2, Nov 2014, pg 16-19
- Vassal Vassileu et al (2008), “Diagnostic Systems in Medicine As Personal Intellectual Tooling”, International Journal “Information Technologies and Knowledge”, Vol.2/2008 . Pg 211-217.
- J.P. Tchapet Njafa, S.G. Nana Engo and P.Woafo (2013), “Quantum Associative Memory for the diagnosis of some tropical diseases”, Cornell University,www.arxiv.org, retrieved 07/04/2015.
- Adeboye K.R and Haruna M. (2015), “A Mathematical Model for the Transmission and Control of Malaria and Typhoid Co-Infection using SIRS Approach”, Researchjournali’s Journal of Mathematics, Vol.2/No2, Pg1-24, February, 2015
- Samuel Oluwarotimi Williams and Omisore Mumini Olatunji (2013), “Genetic Neuro-Fuzzy System for the Diagnosis of Typhoid Fever”, 2013 Conference on Medical Innovation and Computing Service, August 2013.http://www.reseachgate.net/publication/. Retrieved 14/06/15.
- O.Oluwagbemi and B. Oladunni (2010), “Diagnosis and Recommender System for some neglected tropical diseases”, International Journal of Natural and Applied Sciences, 6(2), pg 181-188. www.tapasintitute.org/ journals/ijonas.
Index Terms
Keywords