AI Integration in PACS: Advancing Medical Imaging and Healthcare Delivery

The integration of Artificial Intelligence (AI) into Picture Archiving and Communication Systems (PACS) represents a significant advancement in medical imaging technology. This article examines the transformative impact of AI-enabled PACS on healthcare delivery, focusing on diagnostic capabilities, workflow optimization, and societal implications. Through analysis of implementation case studies, particularly the GE PACS system, we explore how AI integration enhances diagnostic accuracy, improves workflow efficiency, and democratizes healthcare access. The article addresses critical considerations including data security, algorithm bias, and validation protocols, while also examining future implications and providing implementation recommendations. The article demonstrates that AI-enabled PACS systems significantly improve diagnostic accuracy, reduce interpretation times, and enhance healthcare accessibility, particularly in underserved areas, while highlighting the importance of addressing ethical considerations and maintaining robust security measures.

Authors

Publication Details

Journal
International Journal on Science and Technology
Published
2025-03-29
DOI
https://doi.org/10.71097/ijsat.v16.i1.2930
Primary Topic
Digital Radiography and Breast Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

AI Integration in PACS: Advancing Medical Imaging and Healthcare Delivery

Manuel Joy -
International Journal on Science and Technology
Digital Radiography and Breast Imaging
article

AI Integration in PACS: Advancing Medical Imaging and Healthcare Delivery

Manuel Joy -
article en

Abstract

The integration of Artificial Intelligence (AI) into Picture Archiving and Communication Systems (PACS) represents a significant advancement in medical imaging technology. This article examines the transformative impact of AI-enabled PACS on healthcare delivery, focusing on diagnostic capabilities, workflow optimization, and societal implications. Through analysis of implementation case studies, particularly the GE PACS system, we explore how AI integration enhances diagnostic accuracy, improves workflow efficiency, and democratizes healthcare access. The article addresses critical considerations including data security, algorithm bias, and validation protocols, while also examining future implications and providing implementation recommendations. The article demonstrates that AI-enabled PACS systems significantly improve diagnostic accuracy, reduce interpretation times, and enhance healthcare accessibility, particularly in underserved areas, while highlighting the importance of addressing ethical considerations and maintaining robust security measures.

International Journal on Science and TechnologyVol. 16(1)
Openalex Percentile: Top 91%
Digital Radiography and Breast Imaging
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AI Integration in PACS: Advancing Medical Imaging and Healthcare Delivery — Manuel Joy - · International Journal on Science and Technology (2025) | TGRS Research Map | TGRS