Abstract
Malaria disease is a major tropical public health problem in the world. The diagnosis of this type of tropical diseases involves several levels of uncertainty and imprecision. It causes severe infection to the brain and prevents brain from its proper functioning. Hence prior detection of the malaria is much essential. Soft Computing Techniques provide excellent methodologies to process the medical data and help medical experts in finding out the nature of illness and to take decision. True data set collection, feature squeezing, and classification are the basic steps followed in designing an expert system. The designed expert system acts with intelligence, prevents erroneous decisions, and produces sharp results in time. This paper discusses on malaria investigation with missing data using rough set rule-based soft computing technique.
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Panda, B.S., Gantayat, S.S., Misra, A. (2015). Rough Set Rule-Based Technique for the Retrieval of Missing Data in Malaria Diseases Diagnosis. In: Muppalaneni, N., Gunjan, V. (eds) Computational Intelligence in Medical Informatics. SpringerBriefs in Applied Sciences and Technology(). Springer, Singapore. https://doi.org/10.1007/978-981-287-260-9_6
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DOI: https://doi.org/10.1007/978-981-287-260-9_6
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