501The medical world is ever-changing and evolving, and the passage of time brings new opportunities for the advanced use of technology. Such advancements can have major benefits when applied to a medical setting, and a meeting of healthcare representatives in 2018 led to discussion and strategy development about how AI algorithms could be used in radiology. This research was made available to the public on April 16 of this year, and it includes interesting information about where medical radiology may be headed. Below, we’ll walk you through some of the potential benefits outlined in the report so you can learn more about this technological development and how it may someday impact your own radiology practice.
How is AI Used in Medicine Today?
Although the report outlines applications of AI specifically to radiology, artificial intelligence is already being used in the medical world. It is often used for reviewing and searching for relationships in data sets, as well as performing repetitive procedures (like x-rays) and helping select treatment plans for patients. This technology has only grown more advanced over time, which opens up a world of possibilities for radiology practices and providers.
Image Reconstruction and Labeling Techniques
The report outlines priority research areas, which, if pursued, could accelerate advances in the use of AI for radiology. Imaging is a prominent theme in the report, with two of the research priorities focusing on imaging advancements. The use of AI in radiology could bring about new image reconstruction methods, which could lead to the production of images suitable for radiologists to read directly from the source data. Improved image reconstruction would be beneficial for both the providers analyzing the images and their patients. Another research priority is related to automated image labeling and annotation methods. AI advancements in this area could include extracting information from the imaging report, electronic phenotyping, and prospective structured image reporting. The professionals who created the report prioritized these elements of imaging as some which could benefit from the implementation of AI technology in the future.
Advanced Machine Learning Methods
Machine learning techniques could grow even more advanced with the introduction of AI in radiology, and the report outlined two specific areas where machine learning could thrive in the future. AI technology could be used in machine learning methods for clinical imaging data, which could include pre-trained models and distributed machine learning methods. The report also placed an emphasis on the possibility of “explainable artificial intelligence” – machine learning algorithms that could explain their findings to users. This type of advancement would establish an even stronger connection between providers, patients, and the technology used for care.
Data Validation and Accessibility
The last research area prioritized in the report relates to creating validation methods for the de-identification of images and data sharing so that clinical imaging data sets can be more widely available and accessible. The improvement of the availability of validated and reusable data sets would be beneficial to the medical world because this type of accessibility could lead to breakthroughs that were not possible in the past.
Stay Up To Date on Radiology News with HIS
If you are involved in radiology practice, staying up to date on the news of the industry is one of the best ways to properly serve your patients. Future updates about what was stated in the report are sure to come, and at Healthcare Information Services, we look forward to whatever is next. We are proud to offer a number of services for radiology and orthopedic practices, including revenue cycle management, practice management & consulting, coding education, and more. We encourage you to reach out and contact us today to learn more, and stay up to date on the latest industry news through our blog and e-Newsletter.