Main Article Content
Human beings face various diseases due to ecological condition and their living behaviours. So, early prediction of diseases is needed for timely treatment. Data mining based prediction of diseases is considered a promising solution for early prediction. Acquiring knowledge from high-dimensional and heterogeneous medical data is considered a difficult task in data mining. To overcome the difficulties in medical data, deep learning (DL) algorithms are used to extract hidden information accurate from the data set and produce efficient prediction results. In this paper, a complete review of DL algorithms proposed by various researchers in medical data are explained. Then, difficulties in DL algorithms performance and parameters used for evaluating DL algorithms are explained. Finally, preceding suggestions for further research.
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