Big Data Applications and Mining in the Healthcare Field

Authors

  • Fenglong Zhao

DOI:

https://doi.org/10.54097/d9u9iwdzcu

Keywords:

Big Data, Healthcare, Data Mining, Disease Prediction, Clinical Decision Support

Abstract

The healthcare sector faces unprecedented challenges due to global population growth, aging trends, and the continuous outbreak of diseases. This paper explores the significance and potential of big data applications in healthcare. We discuss challenges such as population aging, chronic disease management, and infectious disease transmission, highlighting big data's role in addressing these issues. We examine big data application mining methods, including data collection, storage, preprocessing, cleaning, and analysis, with applications in disease prediction, early diagnosis, clinical decision support, and epidemiological research, illustrated through case studies. Challenges encompass data privacy, ethics, data cleaning, integration, and model interpretability, necessitating continuous technological innovation. Future trends include enhanced data privacy, technological innovation, and interdisciplinary collaboration. Collaboration among research institutions, healthcare organizations, and government agencies is encouraged to advance big data application mining and contribute to healthcare progress. Overcoming challenges and embracing opportunities promises a healthier and more prosperous future.

References

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Xin-Rui Qiu,Xiao-Ning Yan,Lu Chen,Wen-Bin Li. Analysis of effect of external therapies of traditional Chinese medicine on eczema by data mining[J],2021,027(1):49-53

[Ehsan Shirzad,Ghazal Ataei,Hamid Saadatfar. Applications of data mining in healthcare area: A survey[J]. Engineering and Applied Science Research, 2021,48-51

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Published

28-02-2024

Issue

Section

Articles

How to Cite

Zhao, F. (2024). Big Data Applications and Mining in the Healthcare Field. Journal of Computing and Electronic Information Management, 12(1), 27-31. https://doi.org/10.54097/d9u9iwdzcu

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