TRANSFORMING HEALTHCARE THROUGH DATA ENGINEERING, PREDICTIVE ANALYTICS, AND AI MODELS

This article explores how artificial intelligence, predictive analytics, and data engineering have revolutionized contemporary healthcare systems. It investigates how these integrated technologies transform clinical decision-making procedures, operational effectiveness, and patient care delivery. The article examines several topics, such as the fundamentals of data engineering, predictive analytics, AI model architectures, the integration of real-time analytics, and clinical applications. With an emphasis on technical difficulties, data quality control, system integration, and regulatory compliance, it also explores the difficulties and solutions associated with deploying these technologies in healthcare settings. This article illustrates how healthcare organizations use these technologies to move from reactive to proactive care models while enhancing patient outcomes and operational effectiveness through a thorough analysis of current installations and results.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-03
DOI
https://doi.org/10.5281/zenodo.14265469
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

TRANSFORMING HEALTHCARE THROUGH DATA ENGINEERING, PREDICTIVE ANALYTICS, AND AI MODELS

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

TRANSFORMING HEALTHCARE THROUGH DATA ENGINEERING, PREDICTIVE ANALYTICS, AND AI MODELS

article en

Abstract

This article explores how artificial intelligence, predictive analytics, and data engineering have revolutionized contemporary healthcare systems. It investigates how these integrated technologies transform clinical decision-making procedures, operational effectiveness, and patient care delivery. The article examines several topics, such as the fundamentals of data engineering, predictive analytics, AI model architectures, the integration of real-time analytics, and clinical applications. With an emphasis on technical difficulties, data quality control, system integration, and regulatory compliance, it also explores the difficulties and solutions associated with deploying these technologies in healthcare settings. This article illustrates how healthcare organizations use these technologies to move from reactive to proactive care models while enhancing patient outcomes and operational effectiveness through a thorough analysis of current installations and results.

Zenodo (CERN European Organization for Nuclear Research)
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Artificial Intelligence in Healthcare and Education
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