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Research Article · Free to read · Published 17 October 2011

Childhood Cancer-a Hospital based study using Decision Tree Techniques

K. Kalaivani & R. Shanmugalakshmi

Journal of Computer Science, Volume 7, Issue 12, pp. 1819–1823 · doi.org/10.3844/jcssp.2011.1819.1823

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Abstract

Problem statement: Cancer is generally regarded as a disease of adults. But there being a higher proportion of childhood cancer (ALL-Acute Lymphoblastic Leukemia) in India. The incidence of childhood cancer has increased over the last 25 years, but the increase is much larger in females. The aim was to increase our understanding of the determinants of south Indian parental reactions and needs. This facilitates the development of the care and follow-up routines for families, paying attention to both individual risk and resilience factors and to ways in which limitations related to treatment centre and organizational characteristics could be compensated. Approach: Decision Trees may be used for classification, clustering, affinity, grouping, prediction or estimation and description. One of the useful medical applications in India is the management of Leukemia, as it accounts for about 33% of childhood malignancies. Results: Female survivors showed greater functional disability in comparison to male survivors-demonstrated by poorer overall health status. Family stress results from a perceived imbalance between the demands on the family and the resources available to meet such demands. Conclusion: The pattern and severity of health and functional outcomes differed significantly between survivors in diagnostic subgroups. Family impact was aggravated by patients’ lasting sequelae and by parent perceived shortcomings of long-term follow-up. Female survivors were at greater risk for health related late effects.

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Kalaivani, K. & Shanmugalakshmi, R. (2011). Childhood Cancer-a Hospital based study using Decision Tree Techniques. Journal of Computer Science, 7(12), 1819–1823. https://doi.org/10.3844/jcssp.2011.1819.1823

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Childhood Cancer-a Hospital based study using Decision Tree TechniquesJournal of Computer Science · Volume 7, Issue 12 · pp. 1819–1823 · © Science PublicationsDownload