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#RadAIchat T2: I believe AI should be integrated in radiology education, likely in the Physics or #Informatics blocks of education. Not everyone will be interested (like Physics!) but it will be necessary to have some exposure to AI as radiologists. #RadAIchat

#RadAIchat T2: T2: Education can be through a combination of didactic overview lectures, hands-on experiences, Journal Clubs, exercises, and the design, development and assessment of research projects. It may be best received by teaching from clinical perspective, relevance, etc.

#RadAIchat T2: Check out our experience with a Data Science Pathway for Radiology Residents at BWH Radiology in an Radiology: Artificial Intelligence article In Press.

#RadAIchat T2: The article is Preparing Radiologists to Lead in the Era of Artificial Intelligence: Designing and Implementing a Focused Data Science Pathway for Senior Radiology Residents. Wiggins, Caton, Magudia, Glomski, George, Rosenthal, Gaviola, Andriole. Radiology: AI Nov.

#RadAIchat T3: The foundations will remain largely the same. Teach the foundations of data cohort design, data wrangling, data analysis. Methods and tools will evolve and best practices should follow this evolution.

#RadAIchat T3: . For example, current computing, data access, data visualization capabilities and limitations may change and curricula should evolve in these regards. #RadAIchat

#RadAIchat T3: Many of todays apps are using basic vanilla machine learning models, so an understanding of these will be helpful. Understanding cohort design is critical to things like bias, overfitting, imbalance

#RadAIchat T3: Radiology professional societies are creating curriculum content and delivering in a variety of mechanisms: didactic, hands-on, journal clubs and Tweet chats like this!

#RadAIchat T4: Yes – eventually. But it will take some time to become incorporated into the certification process. #RadAIchat

#RadAIchat T4: Felipe Kitamura Similar to the example of not needing to teach Radiologists how to build a CT scanner, but do teach enough about how CT works so that the Radiologist can recognize imaging artifacts and know about patient safety. This should be a competency

#RadAIchat T5: AI can be used as clinical decision support (CDS) at the point of care, and as such is a perfect educational tool. It can be used to remind trainees to include all the pertinent positives and negatives that make up a high quality radiology report.

#RadAIchat T5: AI can be used to pull up cases with similar findings to demonstrate a finding for the trainee. AI can semi-automate report creation thereby teaching the proper content and structure of a report

#RadAIchat T5: It can remind the radiologist interpreter to think of clinical scenarios that may not be common in their practice setting and therefore bring it to their attention. Teach about cases they may never have seen.

#RadAIchat T5: Can we gamify precision education with AI. That would be fun.

I couldn't have asked for a better group of residents to start this data science pathway. Thank you Walter Wiggins, MD, PhD, Travis Caton, MD and Kirti Magudia, MD PhD

Next #MGH & #BWH CCDS Mass General Brigham Data Science Office (DSO) lecture on #AI for clinicians (AI4C) by Felipe Kitamura MD MSc PhD Unifesp on 3/11/21 at noon! Register: eventbrite.com/e/how-to-conne… #informatics

CCDS is hosting their monthly virtual Lecture Series - Artificial Intelligence for Clinicians (AI4C). Join us as we host @DrHughHarvey who will give an overview of the European MDR and FDA pathways for regulating AI software as a medical device. eventbrite.com/e/global-regul…

Changed my Twitter Handle to Kathy Andriole; no longer kpa_kathy

I am definitely biased here... But I think everyone going to #RSNA22 must check out the Imaging AI in Practice Demo (Booth 4329). We've been hard at work putting this demo together since April. The video below will give you a taste of what to expect youtu.be/ZL6BVmIemGg

Mohannad Hussain Kirti Magudia, MD PhD Marta Heilbrun MD MS Walter Wiggins, MD, PhD Charles Kahn, MD Adam Flanders, MD Krishna Juluru @AliTejaniMD RSNA Radiology: Artificial Intelligence RSNA'95 DICOM Demo! Image acquired on vendorA; displayed via vendorB. Demoed that the DICOM image format & communication protocol enabled sharing of digital data between different vendors. The live IAIP demo aims to do the same with AI results; embedding AI in clinical devices.