Data mining and deep learning-based hybrid health care application

The healthcare industry is rapidly changing all across the world. The healthcare industry generates a large volume of diverse data. It is critical for the healthcare industry to effectively get, collect, and mine data. As a result, data mining is used to process vast volumes information on patients,...

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Bibliographic Details
Published in:Applied nanoscience 2023-03, Vol.13 (3), p.2431-2437
Main Authors: Kuruba, Chandrakala, Pushpalatha, N., Ramu, Gandikota, Suneetha, I., Kumar, M. Rudra, Harish, P.
Format: Article
Language:English
Subjects:
Chemistry and Materials Science
Data mining
Deep learning
Health care
Materials Science
Membrane Biology
Nanochemistry
Nanotechnology
Nanotechnology and Microengineering
Original Article
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Summary:The healthcare industry is rapidly changing all across the world. The healthcare industry generates a large volume of diverse data. It is critical for the healthcare industry to effectively get, collect, and mine data. As a result, data mining is used to process vast volumes information on patients, diagnosis, and treatments. Data mining helps physicians to analyze the causes, symptoms, and therapies to discover particular therapy side effects, allowing them to make better judgments and decrease treatment risks. In this paper, we mentioned important problems in healthcare today and also specified different data mining applications in healthcare and reviewed various research works on healthcare applications. Aim of this work is to build a more suitable data mining and deep learning-based hybrid architecture for early detection of breast cancer.
ISSN:2190-5509
2190-5517
DOI:10.1007/s13204-021-02333-1