Empowering Healthcare Professionals: The Role of Cloud-Native Data Engineering in Human-AI Collaboration

This article examines the transformative role of cloud-native data engineering in facilitating human-AI collaboration within healthcare environments. It explores how modern data platforms from major cloud providers enable seamless integration of machine learning models into clinical workflows, supporting healthcare professionals in decision-making while maintaining human judgment as the cornerstone of patient care. The discussion encompasses the technical architecture of healthcare data pipelines, strategies for implementing real-time analytics, and approaches for integrating AI models that complement rather than replace clinical expertise. The article addresses critical challenges, including bias mitigation, data governance, and ethical considerations, advocating for responsible AI deployment that prioritizes patient outcomes. Through the examination of industry case studies and emerging trends, the article provides a comprehensive analysis of how cloud-native technologies are reshaping healthcare delivery while emphasizing the essential partnership between technology innovation and human expertise.

Authors

Institutions

Publication Details

Journal
Journal of Computer Science and Technology Studies
Published
2025-05-15
DOI
https://doi.org/10.32996/jcsts.2025.7.4.50
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Empowering Healthcare Professionals: The Role of Cloud-Native Data Engineering in Human-AI Collaboration

MNV Prasad Gajula
Journal of Computer Science and Technology Studies
Big Data and Business Intelligence
article

Empowering Healthcare Professionals: The Role of Cloud-Native Data Engineering in Human-AI Collaboration

MNV Prasad Gajula
article en

Abstract

This article examines the transformative role of cloud-native data engineering in facilitating human-AI collaboration within healthcare environments. It explores how modern data platforms from major cloud providers enable seamless integration of machine learning models into clinical workflows, supporting healthcare professionals in decision-making while maintaining human judgment as the cornerstone of patient care. The discussion encompasses the technical architecture of healthcare data pipelines, strategies for implementing real-time analytics, and approaches for integrating AI models that complement rather than replace clinical expertise. The article addresses critical challenges, including bias mitigation, data governance, and ethical considerations, advocating for responsible AI deployment that prioritizes patient outcomes. Through the examination of industry case studies and emerging trends, the article provides a comprehensive analysis of how cloud-native technologies are reshaping healthcare delivery while emphasizing the essential partnership between technology innovation and human expertise.

Journal of Computer Science and Technology StudiesVol. 7(4)
Nikkei Business Publications (Japan) (JP)
Openalex Percentile: Top 82%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.