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Research Article Open access CC BY 4.0

Prediction of Accuracy in Emergency Health Records using Hybrid Machine Learning Model

G. S. Raghavendra, Shanthi Mahesh, M. V. P. Chandra Sekhara Rao

Journal of Pharmaceutical Research International · pp. 206–212 · Published 15 Dec 2021

10.9734/jpri/2021/v33i58A34107

Abstract

The quantity of digital information contained in electronic health records(EHR) has increased dramatically during the last ten years. Numerous researchers have discovered that these records may be used for a variety of other purposes as well, including applications in clinical informatics. Additionally, within the same time period, significant advancements in the area of deep learning have been made by the machine learning community. Using EHR data, we examine the existing research on applying deep learning to clinical activities. In this article we will discuss various deep learning techniques used for the classification of electronic health records along with proposing of Hybrid model for finding classification accuracy of various models.

MHR CNN botlzmann machine hybrid model naïve bayes

Cited by 1

A Framework for Blended Sub Feature Engineering for Chronic Disease Prediction Using in-Memory Computing

Gunturi S. Raghavendra, Shanthi Mahesh, Manukonda Venkata Poorna Chandrasekhara Rao · Revue d intelligence artificielle · 2022

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