You really think radiologists would evolve into this just to get replaced by AI? Not a chance.

Several years ago, I expected the leading hardware and PACS vendors to drive consolidation in radiology AI. RadNet, however, continues to roll up breast AI vendors (last month iCAD, Inc.) with its purchase of breast US/thyroid AI and reporting company See-Mode Technologies.

JP's work at NYU Langone Health Department of Radiology with Krzysztof Geras was integral to developing our clinical DBT AI algorithm (among many other great projects). I am proud to finally call Jungkyu Park Dr. Park after his PhD defense. He has earned it and I look forward to seeing what he contributes to the

In some ways, the future of radiology.

I am once again pitching my romantic comedy: - two academics start dating - discover they are each other's terrible reviewer - hijinks ensue Working title: Love is Double-Blind

Great commentary on the current state of AI in radiology: “ …if you define jobs in terms of tasks maybe you're actually defining away the most nuanced and hardest-to-automate aspects of jobs, which are at the boundaries between tasks.” I do use AI daily, and those messy edges

Things radiology AI researchers should be working on solving ASAP before publishing more garbage CXR research. Thyroid US. LDCT Screening exams. IPMN fu exams. Bone surveys. Standing scoliosis series. Post op spine exams Pranav Rajpurkar Laura Heacock, MD Stephen Borstelmann MD Dr Amine Korchi

Nikhil Krishnan All healthcare startups are either a labcorp adjacent wrapper or a drug newly approved for new disease market wrapper or both

Too many em dashes? What’s next? too much love? too much joy?

Hear me out: Get rid of the wellness modules — instead: once a year, the inflatable jousting cage comes out. You’re sent in with people randomly selected from the services you interact with, and finally get a chance to “thank them for this interesting consult”.

I take it back, AI is coming for academic jobs.

This year at #RSNA2025 our team at NYU Langone Health Department of Radiology Center for Advanced Imaging Innovation & Research is presenting on our breast multimodal model (MG/US/MRI) with external validation, and its use in high-risk women for cancer detection and long-term risk prediction. We also have a presentation on our exciting new

I want to also give credit to phenomenal NYU Grossman School of Medicine MS3 Felicia Pasadyn and NYU Langone Health Department of Radiology resident Samantha Platt who both took ownership of their projects and have first-author #rsna2025 accepted abstracts as a result.