Effectiveness of machine learning and artificial intelligence in formulating radiological reports for faster and more reliable diagnostics
Mahatma Gandhi Medical College and Research Institute, Puducherry, India.
Review
World Journal of Biology Pharmacy and Health Sciences, 2024, 19(01), 419–422.
Article DOI: 10.30574/wjbphs.2024.19.1.0461
Publication history:
Received on 16 June 2024; revised on 26 July 2024; accepted on 28 July 2024
Abstract:
This article explores the transformative impact of machine learning (ML) and artificial intelligence (AI) on radiological investigations. By enhancing diagnostic accuracy and efficiency, AI algorithms especially deep learning models can detect abnormalities in medical images with remarkable precision, often surpassing human radiologists. The integration of AI expedites image analysis and report generation, alleviating radiologist workloads and reducing burnout. AI systems also offer consistent reporting and continuous learning, improving their performance over time through exposure to vast datasets. Despite the significant benefits, challenges such as data privacy, security, and the need for rigorous validation and oversight remain. As AI continues to advance, it is poised to play a crucial role in enhancing patient care and outcomes in radiology.
Keywords:
Radiology; Artificial Intelligence; Machine Learning; Algorithms; Data
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0