The week's pick
Random Articles
Reseach Article
An Intelligent Approach to Reducing Tobacco Smoking among Adolescents: Health Risk Expert Approach
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 153 - Number 7 |
| Year of Publication: 2016 |
| Authors: Hyellamada Simon, Benson Yusuf Baha, Nachandiya Nathan |
10.5120/ijca2016912102
|
Hyellamada Simon, Benson Yusuf Baha, Nachandiya Nathan . An Intelligent Approach to Reducing Tobacco Smoking among Adolescents: Health Risk Expert Approach. International Journal of Computer Applications. 153, 7 ( Nov 2016), 23-28. DOI=10.5120/ijca2016912102
Abstract
Tobacco smoking causes health challenges both nationally and internationally, and there is need to reduce tobacco consumption. To achieve this, the researchers used Case Based Reasoning (CBR) methodology and Nearest Neighbour (NN) similarity technique in developing a web-based expert system to assist in reducing the rate of tobacco consumption among adolescents. In the cause of the research, 20 related diseases to tobacco smoking were identified and stored in the knowledge based; these data were used to test 3 new cases and their inherent individual level associated to it. The new cases are tuberculosis, laryngeal cancer (throat cancer), and asthma with highest risk values of 1.0, 0.8, and 0.9 respectively. The results provided a procedure to assist adolescents (smokers) minimize tobacco consumption. The system also offers some home remedies to help them deal with nicotine withdrawal syndrome. Therefore, adolescents are advised to quit smoking in order to avoid serious health problems in the future.
References
- Aamodt, A., & Plaza, E. 1994. Case-based reasoning: Foundational issues, methodological variations, and System approaches. AI Communications. 7. 39-59.
- Action on Smoking and Health. 2012. ASH Research Report on Tobacco and Oral Health. Retrieved 19th January, 2016, from http://www.ash.org.uk/files/documents/ASH_598.pdf
- Action on Smoking and Health. 2013. ASH Research Report on Smoking and Cancer. Retrieved 19th January, 2016, from http://www.ash.org.uk/files/documents/ASH_109.pdf
- Ahmed, M. U., Begum, S., Funk, P., Xiong, N., &Scheele, B. V. 2008. Case-Based Reasoning for diagnosisof stress using enhanced cosine and fuzzy similarity.Journal of IBaI Publishing. 1(1). 3-19.
- Begum, S. 2009. A case-based reasoning system for theDiagnosis of individual sensitivity to Stress in psychophysiology. Malardalen University Press Licentiate Theses. ISBN 978-91-86135-25-6.
- Brunette, M. F., Gunn, W., Alvarez, H., Finn, P. C.,Geiger, P., Ferron, J. C., McHugo, G.J. 2015. A pre-post pilot study of a brief, web-based intervention toengage disadvantaged smokers into cessation treatmentAddiction Science & Clinical Practice. 10(3).Doi:10.1186/s13722-015-0026-5.
- De-mantaras, R. L., Mcsherry, D., Bridge, D., Leake, D.,Smyth, B., Craw, S., …, Watson, I. 2005. The Knowledge Engineering Review. Cambridge University Press.00(0).1-2. Doi:10.1017/S000000000000000.
- Ekerholt, M., Folleso, S. L., Heimark, O. 2014. A Systemfor Conversational Case-Based Reasoning in Multiple Disease Medical Diagnosis. Master’s Thesis, Norwegian University of Science and Technology.
- Haris, M. F. 2012. Diagnosing hepatitis using hybridfuzzy-CBR. Master degree Dissertation. University Utara Malaysia.
- Hole, K. R., & Gulhane, V. S. 2014. Rule-Based ExpertSystem for the Diagnosis of Memory Loss Diseases. IJISET. 1(3). 2348–7968.
- Kabulwa, M. N. 2011. Prevalence, perceived factors andknowledge on effects of tobacco use on oral health among secondary school students in dares salaam. Master’s degree Dissertation. Muhimbili University of Health and Allied Sciences.
- Kohler, B. A., Ward, E., McCarthy, B. J. 2011. Annualreport to the nation on the status of cancer, 1975–2007, featuring tumors of the brain and other nervous system. JNatl Cancer Inst. 103(9). 714-736.
- Kolodner, J.L. 1993. Instructional design: Case Base Reasoning. Morgan Kaufmann Publishers, San Mateo, CA.
- Mary, T. W., Kaplan, B., Connoly, S. W., Michel, G.,Shiffman, R. N., & Flynn, B. S. 2008. Developing a Decision Support System for Tobacco Use Counseling Using Primary Care Physicians. Inform Prim Care. 16(2).101–109.
- Mathew, S. Shilu, M., Hamed, M. H., & Qadri, I. 2015. A web based decision support system driven for the Neurological disorders. IJERGS. 3(4).
- Mohasoa, I. P. 2010.Substance abuse among male adolescents. Master’s degree Dissertation. University of South Africa.
- Oxford Medical Dictionary. 2002. Oxford University press Britain. (6th ed.).
- Patel, M. & Virparia, P. 2013. Rule Based Expert System for Viral Infection. IJARCSSE. 3(5).
- Prochaska, J., O., Velicer, W. F., Fava, J. L., Ruggiero,L., Laforge, R. G., Rossi, J. S., Lee, P. A. 2001. Counselor and Stimulus Control Enhancements of a Stage-Matched Expert System Intervention for Smokers in a Managed Care Setting. Cancer Prevention Research Center. University of Rhode Island. 32. 23-32. doi:10.1006/pmed.2000.0767.
- Salem, A. M., Roushdy, M., &HodHod, R. A. 2005. A case based expert system for supporting diagnosis of heart diseases. AIML Journal. 5(1).
- Schank, R. C. 1983. Dynamic memory: A theory of reminding and learning in computers and people. Cambridge University Press.
- Schmidt, L. 2014. Health harms from smoking and other tobacco use. Campaign for Tobacco-Free Kids. Retrieved from http://www.tobaccofreekids.org/facts_issues/fact_ sheets/toll/products/.
- U.S Department of Health and Human Services 2010.The Health Effect of Tobacco. Retrieved 19th January, 2016, from www.cdc.gov/tobacco/data_statistics/sgr/2010/consumer_booklet/pdfs/consumer.pdf
- World Health Organization 2015.Global Report on Trends in Prevalence of Tobacco Smoking. WHO Library Cataloguing-in-Publication. Publication Number 978 92 4 156492 2 (NLM classification: WM 290).
Index Terms
Keywords