A Thorough Examination of AI Integration in Diagnostic Imaging

Author:

Paul Shyamalendu1ORCID,Purkait Soubhik1,Chowdhury Pritam1,Ghorai Siddhartha1,Mallick Sohan1,Nath Somnath1

Affiliation:

1. Brainware University, India

Abstract

Examining how artificial intelligence might be used in diagnostic imaging, this study explores its significant healthcare ramifications. The chapter highlights the crucial role that AI plays in enhancing diagnostic accuracy, speed, and efficiency in the interpretation of medical imaging data while shedding light on the implementation of deep learning and machine learning algorithms in this context and offering examples. One of the most crucial things to consider is research on the long-term therapeutic impacts of AI integration. Transparent and understandable AI models must be created to foster trust between patients and healthcare professionals. The study also encourages a comprehensive evaluation of AI models' real-world performance across a range of imaging technologies, healthcare systems, and populations. The study essentially highlights the numerous advantages of integrating AI into diagnostic imaging, imagining a revolutionary environment that is promising for patients and healthcare providers alike.

Publisher

IGI Global

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