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"Considering a donation to the RSNA R&E Fund? Over 40 years, it's supported radiologists and trainees with over $84M in grants, shaping careers like mine. I'm truly honored to have received one. #ProudRecipient #RadiologyResearch"

Featuring Malone researchers Suchi Saria, Chien-Ming Huang, and Paul Yi:

Become a radiology leader of tomorrow! Johns Hopkins Radiology residency programs offer exceptional, hands-on training and support under world-renowned expert faculty. Experience the Johns Hopkins difference for yourself! Learn more at hopkinsmedicine.org/radiology/educ….

I’m thrilled to share two of my articles in the American Journal of Roentgenology were selected among the best submissions of 2024! It’s been incredible collaborating with researchers as we explore the impact of AI in radiology. ajronline.org/doi/10.2214/aj…

In the November 2024 RSNA Radiology Journal, Dr. Paul H. Yi and a team of multicenter researchers explored how AI explanations impact physician decision-making when reading chest X-rays. pubs.rsna.org/doi/epdf/10.11…

When do AI explanations actually help, & promote appropriate trust? Spoiler, via prospective, multisite Radiology study of 220 doctors: *How* AI explains its advice has big impacts on doctors’ diagnostic performance and trust in AI--even if they *don’t realize it*! 🧵1/

🌟 I'm excited to announce that I've started my new role as Chief Strategy Officer and Chief Medical Information Officer at HOPPR! 🚀 I will be joining William Boonn and John Paulett. I met Khan M. Siddiqui, MD, when I did my imaging informatics fellowship in 2006. We, along with Nabile Safdar,

Make sure to attend the closing session of #SIIM25 to witness the ultimate showdown between #AI and humans! This interactive, game-show-style keynote will feature Kathy Andriole, Richard Wiggins, LLM Mastermind, and YOU! Learn More | vist.ly/3mya44v Register |

Over 1,000 clinicians have assessed MedArena LLM performance for their medical questions. #MedTwitter Try it! medarena.ai/login James Zou

A new study by Hopkins researchers including the Malone Center’s Suchi Saria and Paul Yi finds that doctors’ diagnostic performance and trust in #AI advice depends on just how exactly the AI assistant explains itself. Learn more: malonecenter.jhu.edu/explain-yourse…

🚀 Let’s take imaging informatics to New Heights at #SIIM25! I’ll be speaking on Human #AI Collaboration in Radiology and would love to see you there. 📅 May 21–23 📍 Portland, OR 🔗 annualmeeting.siim.org

Last but certainly not least, the #MSS talks with Paul Yi, Alex Towbin (He/Him), and Tessa S. Cook MD PhD CIIP FSIIM FCPP FAAR on the past, present, and future of technology in radiology. So valuable to be able to engage with these topics as #futureradres. American College of Radiology ACR RFS - We've Moved! Follow @RadiologyACR. #ACR2025 Josh Baker, PhD Bryant Chang, MD

Will we be replaced? No. But will we be transformed? Yes. ✨ Huge thanks to Paul Yi, Alex Towbin (He/Him) & Tessa S. Cook MD PhD CIIP FSIIM FCPP FAAR for leading this #ACRMSS session on the past, present and future of radiology and AI. #ACR2025

Personal highlight this morning at #ACR2025 MSS: panel discussion from Paul Yi, Alex Towbin (He/Him), and Tessa S. Cook MD PhD CIIP FSIIM FCPP FAAR on #radiology and AI tools. Inspiring to see where we’re headed, and proud to be entering a field driven by innovation, informatics, and data-driven care. #radsresearch

Paul Yi recently joined Alex Towbin (He/Him) and Tessa S. Cook MD PhD CIIP FSIIM FCPP FAAR as they presented, “Imaging the Future: A Med Student's Guide to Radiology's Past, Present, & Future-Where AI in Radiology Has Been, Where It Is Currently, & Where It May Be Going” at #ACRMSS #ACR2025 St. Jude Research

How can we tell if AI is truly fair in radiology? 🧠This study by Paul Yi et al unpacks the big challenges in evaluating algorithmic bias, from inconsistent definitions to missing demographic data. A must-read for building better, more equitable models. pubs.rsna.org/doi/10.1148/ra…

Pitfalls & pearls: experts on AI in radiology discuss best practices when evaluating algorithm bias Paul Yi St. Jude St. Jude Research Linda Moy Beepul Bharti Adway Kanhere @garin_SP Pranav Kulkarni Vishwa Parekh Samantha Santomartino Jeremias Sulam JHU Malone Center for Engineering in Healthcare Johns Hopkins BME bit.ly/45jxkdu

Working with students like Rachel Ivy is one of the best parts of my job. They are so inspiring to me and it's a joy to be a part of their journeys. Huge thanks to RSNA & St. Jude for supporting these rising stars in #Radiology, #AI, & #Research! The future is bright! 😎