Enhancing Diagnostic Accuracy: The Role of AI in Advanced Radiological Imaging
This paper investigates how clinical technologies focusing in radiology enriched by AI technologies have emerged as a pivotal advancement in the field of radiology, offering advancements that enhance both diagnostic accuracy and operational efficiency. These AI systems improve diagnostic performance by identifying subtle patterns that might be overlooked by human radiologists. Additionally, AI integration with Picture Archiving and Communication Systems (PACS) streamlines image management, automating routine tasks such as image analysis and report generation, which boosts workflow efficiency and productivity. Despite these benefits, challenges such as data privacy, algorithm transparency, and the need for continuous validation of AI models remain pertinent. As AI technology evolves, it holds the promise of further enhancing radiological practices, improving patient outcomes, and contributing to a more efficient healthcare system.
Authors
- Chiang Liang Kok (ORCID: https://orcid.org/0009-0007-7368-1280)
- Yit Yan Koh
- Tee Hui Teo (ORCID: https://orcid.org/0000-0003-2123-9347)
- Nguyen Van Thanh (ORCID: https://orcid.org/0000-0003-3761-5706)
- Chee Kit Ho
Institutions
- Singapore University of Technology and Design (SG)
- Singapore Institute of Technology (SG)
- University of Newcastle Australia (AU)
Publication Details
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1109/tencon61640.2024.10903067
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.12