Rashidul Hasan Nabil
ABSTRACT
Many machine learning approaches have been applied in order to predict different types of diseases over last few years. Early diagnosis and prognosis depending on these predictions have become very necessary for further treatment policy in different sectors. Moreover, in order to predict something like these diseases or abnormality might need real-life data interaction. The importance of these predictions has led many researchers to study bioinformatics and machine learning. However, selecting correct attributes to design prediction models is also necessary. In this paper we have introduced an approach where several machine learning models will be fitted with the related attributes while performing the predictions from data interaction.
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Index Terms
- Blood Count Prediction for Disease Prognosis based on Combined Multi-modal Interaction Model with Related Attributes
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