Radiology, AI, and Patient Outcomes
At the recent RSNA annual meeting in Chicago, imaging leaders called on radiologists to play a bigger role in patient outcomes. During a plenary session, RSNA president Dr. Bruce Haffty and Dr. Elizabeth Morris from UC Davis Health addressed the need for radiologists to take ownership of patient care and look at things from the patient’s perspective. Both physicians shared personal experiences that highlighted the importance of imaging during a patient’s health journey.
Dr. Morris stressed that ownership of patient care includes addressing findings on radiology exams and asked who is responsible for incidental findings discovered during imaging exams. She feels this is an opportunity for radiologists to be more involved in patient care, advocating for needed tests and follow-up care.
As radiologists embrace this shift in roles, what tools are available to help them? The use of artificial intelligence (AI) is rapidly becoming the norm for radiologists, helping to improve workflow efficiency, diagnostic ability, and patient outcomes across a variety of therapeutic areas. This week’s Domain Knowledge highlights different AI tools available to support radiologists as they provide patient care.
- Real-world examples using artificial intelligence to impact patient care
- AI Trends in Diagnosing Colorectal Cancer
- Using AI to Improve Efficiency and Equity in Cervical Cancer Screening
- Cancer Prevention Gets a Boost from AI
That’s a wrap for this week’s review of news and happenings in the healthcare AI space. In closing, I’ll leave you with an invitation to learn more about the benefits of using an AI Hub to manage multiple applications across your clinical needs and offer you a personal demo of Ferrum’s platform and growing AI catalog.
If you have AI tips, suggestions, or resources, you’d like to share, leave us a note below, and please feel free to suggest topics you would like to see covered in future posts.