The Role of Predictive Analytics in Disease Prevention : A Technical Overview

This article explores the transformative potential of predictive analytics in healthcare, focusing on its applications in disease prevention and public health management. It examines the power of data integration from diverse sources, the use of predictive modeling for risk stratification, and the broader implications for public health surveillance and chronic disease management. The article also discusses the significant growth of AI in the healthcare market and highlights successful implementations of predictive analytics across various medical domains. Additionally, it addresses the key challenges in implementing these technologies, including data privacy concerns, integration issues, model accuracy, and ethical considerations. Through numerous case studies and statistical evidence, the article demonstrates how predictive analytics is revolutionizing healthcare by enabling more accurate, personalized, and proactive approaches to disease prevention and management.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2024-11-08
DOI
https://doi.org/10.32628/cseit24106174
Citations
2
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
1.42
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article

The Role of Predictive Analytics in Disease Prevention : A Technical Overview

Harpreet Singh
2 citations
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Artificial Intelligence in Healthcare
1.42
article

The Role of Predictive Analytics in Disease Prevention : A Technical Overview

Harpreet Singh
article en
2 citations

Abstract

This article explores the transformative potential of predictive analytics in healthcare, focusing on its applications in disease prevention and public health management. It examines the power of data integration from diverse sources, the use of predictive modeling for risk stratification, and the broader implications for public health surveillance and chronic disease management. The article also discusses the significant growth of AI in the healthcare market and highlights successful implementations of predictive analytics across various medical domains. Additionally, it addresses the key challenges in implementing these technologies, including data privacy concerns, integration issues, model accuracy, and ethical considerations. Through numerous case studies and statistical evidence, the article demonstrates how predictive analytics is revolutionizing healthcare by enabling more accurate, personalized, and proactive approaches to disease prevention and management.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 10(6)
Gilead Sciences (United States) (US)
Openalex Percentile: Top 13%
Artificial Intelligence in Healthcare
1.42
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