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Check out our work published this week in Science Robotics!

New work with Stephanie McNamara & Paul Yi. We study explainability & intended use in FDA-cleared AI for medical image interpretation. We create a curated database and find a high prevalence of triage devices, meaningful variation in basic outputs, and often limited explainability

Exceptional work Stephanie McNamara evaluating utilization of arterial and venous thrombectomy in the US 🤩 #bigdata

Excited to announce our newly matched IR/DR residents! Welcome to the MGH IR family! Shen Ning, MD, PhD Stephanie McNamara Prateek Gowda MGH Radiology Chiefs SIR RFS #Match2024 #IRadres #futureradres

📢 Introducing our newest residents! We are thrilled to have you join us and cannot wait until you are here! 📷 Happy Match Day! #MatchDay2024 #FutureRadRes #RadRes MGHIR

Congratulations to the amazing MD-PhD Class of 2024 on achieving the matches of their dreams!♥️ “Kid[s], you’ll move mountains! Today is your day! Your mountain is waiting. So get on your way!” (from Oh, The Places You’ll Go! by the good doctor Seuss). Next stop: Graduation!

A curated database of U.S. FDA-cleared #ArtificialIntelligence products for medical imaging indicates a high prevalence of triage systems, variability in basic output characteristics, and often limited #explainability of AI predictions. nature.com/articles/s4174…

Check out our work published this week in npj Digital Medicine! Bill Lotter Paul Yi

Our review on AI in Oncology is out today in Cancer Discovery!

Excited for "Acquisition parameters influence AI recognition of race in chest x-rays and mitigating these factors reduces underdiagnosis bias" to finally come out in Nature Communications nature.com/articles/s4146… (1/n)