Machine Learning in Smart HealthCare Industry

Lithu Mathew; Kala O S

Machine Learning in Smart HealthCare Industry

Authors: Lithu Mathew, Kala O S

Unique Paper ID: 154168
Volume: 8
Issue: 7
PageNo: 27-31

Keywords: Convolution neural network structured data Data imputation

Abstract:
Chronic disease prediction plays an important role in healthcare informatics. It is crucial to diagnose the chronic disease at an early stage. In the field of healthcare communities, the accurate analysis and prediction plays the major role tofind out the risk of the disease in the patient. However, the analysis of accuracy is reduced, and it leads to less accuracy of prediction when the quality of data is incomplete and the poor condition of the medical data. We seek machine learning techniques for effective prediction of chronic disease. We propose to use convolution neural network algorithm for structured and unstructured data. The accuracy obtained using CNN model reaches 94.8% and none of the existing algorithm focuses on structured and unstructured data in the area ofmedical data analytics.

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Cite This Article

ISSN: 2349-6002
Volume: 8
Issue: 7
PageNo: 27-31

Machine Learning in Smart HealthCare Industry

Available:https://ijirt.org/Article?manuscript=154168

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Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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