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Data mining techniques for Medical Growth: A Contribution of Researcher reviews


M.N. Sohail, Ren Jiadong, M.Irshad, M.M.Uba, S.I. Abir


Vol. 18  No. 10  pp. 5-10


Since the last decade, data mining is contributing nicely and becoming very rich in different industries, especially data mining is working tremendously in healthcare section to predict the different life taking diseases on time. The introduced applications in data mining can be classified in to two subsets: the set of policy development and the set of decision-making or the decision support. By the huge amount of work in data mining but still it is hard to discover the priceless literature in the area of this technology under healthcare. During the research, number of papers has been reconsidered in this manifesto and comprises them in to the single platform for better reviews and understanding in term of saving time and efforts in terms of schemes, algorithms, techniques and results. This paper comprises the contribution of various researchers of healthcare sectors in a single platform under data mining categorization for predictions and decision-making by elaborating and mentioning different techniques and algorithms working out since decade to cure the life taking diseases like Breast cancer, Heart attacks, HIV, Lungs cancer, Skin infections with their mean accuracy by defining various studies.


KDD, data mining in healthcare, algorithms, techniques, lung cancer, breast cancer, diabetes, skin diseases, heart diseases.