A Survey on Advanced Approaches of EHR in inter-related data using Machine Learning

Journal Title: Annals of Computer Science and Information Systems - Year 2018, Vol 14, Issue

Abstract

Medical data is being used for huge number of research works over the globe which is for predicting something novel case studies in each work. The current research which we are handling is on utilizing the EHR (Electronic health Records) data in an efficient way based on the cause -- effect ratio and the variables available for the data manipulation, processing and generating efficient data for designing efficient prediction models. In this research we are focusing on the congenital tethered cord syndrome through which some many functional outcomes issues are recording in different cases and there is a wide range of scope for research. In this research we are identifying the data from different EHR applications and designing the architecture to gather valuable data set from those for designing prediction model for predicting functional outcomes of health and life in patients with congenital deformity. Through EHR applications we gather information and BigData is being created in this sector. Data inter --relation is explained in this survey article in an efficient way with respect to medical domain. EHR data will be hosted over the cloud and in public repositories. Will focus on those categories in an efficient manner.

Authors and Affiliations

T. V. M. Sairam, R. Rajalakshmi

Keywords

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  • EP ID EP569738
  • DOI 10.15439/2017KM10
  • Views 18
  • Downloads 0

How To Cite

T. V. M. Sairam, R. Rajalakshmi (2018). A Survey on Advanced Approaches of EHR in inter-related data using Machine Learning. Annals of Computer Science and Information Systems, 14(), 113-119. https://europub.co.uk/articles/-A-569738