Honored to share that our paper (https://t.co/upDJr0nW0v) was selected as Radiology’s Top 10 Most-Cited Articles of 2025 (#3)
Thank you to everyone who contributed, collaborated, and supported this work along the way.
Radiology’s Top Articles of 2025: https://t.co/pK3gMxFIBH
Excited to share that I’ve been appointed to the SIIM Machine Learning Tools & Research Subcommittee. I’m grateful for the opportunity and eager to collaborate with talented fellow committee members and push ML in informatics forward!
@SIIM_Tweets#Radiology#AI
🚨 New episode of the @Radiology_AI podcast is now available! 🚨 @PaulYiMD & @AliTejaniMD welcome new team members @Khosravi_Bardia & @CodySavRad to discuss AI-generated podcasts, Google’s Notebook LM, and the future of radiology education. https://t.co/b7dklEJwa7
@woojinrad Very cool. I'm interested to see the unique applications of sentence embedding diffusion models (RL pipelines?). Between this and their Byte latent transformer they've been on a role with tackling the tokenization problem.
This prospective real-world study found clinical implementation of an AI triage system improved radiologists' sensitivity for incidental pulmonary emboli detection on contrast-enhanced CT examinations of the chest or abdomen.
https://t.co/6SJm7PTUle
This large prospective real-world study found a widely used AI triage system failed to improve radiologists' accuracy for intracranial hemorrhage detection on noncontrast head CT examinations.
https://t.co/Z29J8P4PLk
While Ali (the lead author) and I are an n=1, the results held true for us! So glad to be able to work on this paper with you, and more importantly, to now call you my wife.
I’m excited to announce that two of our studies have been accepted to @AJR_Radiology and featured on their YouTube series. Extremely grateful and can’t thank Andrew Smith and Steven Rothenberg enough for their mentorship.
1️⃣ https://t.co/jE3Wev68Vs
2️⃣ https://t.co/4dfzchNfgK