Advancing Healthcare Through Data: A Comprehensive Analysis of Predictive Modelling and Insights

The integration of data analytics and predictive modeling has revolutionized the healthcare landscape, enabling healthcare providers to anticipate patient needs, allocate re- sources more efficiently, and implement preventive measures. The proposed work explores the applications and implications of healthcare analytics and predictive modeling in contemporary healthcare settings. A comprehensive literature review and in- depth analysis of real-world healthcare environments reveals the critical role of predictive modeling in shaping modern healthcare practices. The findings highlight the effectiveness of predictive analysis techniques in identifying patient outcomes and optimizing healthcare delivery, while also identifying challenges and opportunities associated with implementation. Recommendations for leveraging healthcare analytics to drive actionable insights and improve patient care are proposed. This research aims to identify the disease and minimizing the hospital human resources. This paper aims to create analytical model in healthcare sector for transforming traditional healthcare practices into potential healthcare predictive modelling system, which can further revolutionize patient care and optimizing the health care resources.

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Publication Details

Journal
International Research Journal on Advanced Engineering Hub (IRJAEH)
Published
2025-09-23
DOI
https://doi.org/10.47392/irjaeh.2025.0520
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Advancing Healthcare Through Data: A Comprehensive Analysis of Predictive Modelling and Insights

International Research Journal on Advanced Engineering Hub (IRJAEH)
Artificial Intelligence in Healthcare
article

Advancing Healthcare Through Data: A Comprehensive Analysis of Predictive Modelling and Insights

article en

Abstract

The integration of data analytics and predictive modeling has revolutionized the healthcare landscape, enabling healthcare providers to anticipate patient needs, allocate re- sources more efficiently, and implement preventive measures. The proposed work explores the applications and implications of healthcare analytics and predictive modeling in contemporary healthcare settings. A comprehensive literature review and in- depth analysis of real-world healthcare environments reveals the critical role of predictive modeling in shaping modern healthcare practices. The findings highlight the effectiveness of predictive analysis techniques in identifying patient outcomes and optimizing healthcare delivery, while also identifying challenges and opportunities associated with implementation. Recommendations for leveraging healthcare analytics to drive actionable insights and improve patient care are proposed. This research aims to identify the disease and minimizing the hospital human resources. This paper aims to create analytical model in healthcare sector for transforming traditional healthcare practices into potential healthcare predictive modelling system, which can further revolutionize patient care and optimizing the health care resources.

International Research Journal on Advanced Engineering Hub (IRJAEH)Vol. 3(09)
Institution of Electronics and Telecommunication Engineers (IN)
Openalex Percentile: Top 71%
Artificial Intelligence in Healthcare
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