Publication details
Výzvy a důsledky využití umělé inteligence v radiologii
| Authors | |
|---|---|
| Year of publication | 2023 |
| Type | Chapter of a book |
| Citation | |
| Description | Message for practice The development of artificial intelligence (AI) in medical imaging presents many challenges and opportunities. AI can help physicians in diagnosis, detecting pathologies and improving image quality. If we understand its role as a supportive tool to augment and improve the physician‘s evidence base for informed decision making, rather than as a substitute for the physician, these technologies can make a significant contribution to improving the quality of healthcare that will benefit patients, healthcare professionals and operators. The following attempts to outline some of the challenges associated with their use. Fundamental is the recognition that the accuracy of a model and its ability to provide predictions is dependent on the quality of the data on which it is trained. If the training data is inaccurate, incomplete or biased, it can have a negative impact on the accuracy of the model, especially if there is systematic error. In situations where a population group is under-represented in the training data, biased and potentially damaging predictions may result. It is important that models are transparent, so that clinicians can understand what their decisions are based on and can trust their recommendations. However, for AI to be truly effective and beneficial to physicians, it is essential that it be seamlessly integrated into existing clinical processes so that it does not increase physician workload. We also briefly discuss the general principles of AI regulation in radiology and the specific form of regulation in the EU. |