Artificial Intelligence: Lessons Learned from Radiology

Abstract

Artificial intelligence (AI) will continue to increase its significant impact on the everyday acquisition, interpretation, and application of data in our healthcare system. It is difficult to predict whether and to what extent AI will change the health status of patients, but it certainly will change the way decisions are made, how healthcare is delivered, and the ways providers, patients, and healthcare enterprises interact with and use data from an increasing array of sources. Radiology has often been at the forefront of technological change in healthcare and the AI revolution is no different. The lessons radiology has learned to date, its successes and challenges, can help provide guidance for other specialties, especially since radiology interacts with and cross-cuts nearly every other specialty and touches nearly every patient at least once in his or her lifetime.

Legal issues in digital oral health: a scoping review

“…Oral health practitioners are recommended to familiarise themselves with the relevant guidelines, or even obtain legal advice, on the technological and ethical aspects of digital oral health [ 30 ] and remain aware of the legal requirements of the jurisdiction of practice. For example, at present, there are no well-defined regulations in place to address the legal and ethical issues that may arise due to the use of artificial intelligence and machine learning in health [ 62 ]. “Cloud” technology is another example impacted by lack of clear guidelines [ 63 ].…”

Revolutionizing Pulmonary Diagnostics: A Narrative Review of Artificial Intelligence Applications in Lung Imaging

“…Collaborating with subject matter experts is crucial to effectively address complex medical challenges by combining AI expertise with domain-specific knowledge [ 48 ]. Rigorous validation and testing processes are essential to guarantee the reliability and generalizability of AI algorithms in medical imaging applications [ 49 ]. Fostering a culture of continuous learning and improvement is essential for overcoming challenges and optimizing the integration of AI in healthcare settings [ 50 ].…”

“…Fostering a culture of continuous learning and improvement is essential for overcoming challenges and optimizing the integration of AI in healthcare settings [ 50 ]. Addressing ethical considerations, such as bias mitigation, privacy protection, and transparency, is fundamental to deploying AI solutions responsibly in medical imaging [ 49 ]. Leveraging expertise from various disciplines, including radiology, computer science, and medical physics, enhances the development and implementation of AI technologies in medical imaging [ 50 ].…”