Detection of Tumors from Computed Tomography Scans Early and Pre-diagnostic https://t.co/CjOmkhDwva

Fall 2025 GRASP on Robotics - Alan Yuille, Johns Hopkins University

Check out the AI powered radiology reporting at #ICCV2025

🤯 Think better visuals mean better world models? Think again. 💥 Surprise: Agents don’t need eye candy— they need wins. Meet World-in-World, the first open benchmark that ranks world models by closed-loop task success, not pixels. We uncover 3 shocks: 1️⃣ Visuals ≠ utility 2️⃣

🚨 Call for posters! 🚨 Submit your engineering healthcare research for our annual symposium. ✅ Submission form: https://t.co/vn3J7xBsoL 🗓️ Deadline: November 10, 2025 @ 11:59 p.m. Learn more about the symposium: https://t.co/ddPM1iRdoW

Starting at 4:00 PM in Room 323A — I’ll share how medical reports can revolutionize dataset curation, annotation, and small-tumor detection, while improving AI generalization across cancers. See slides here https://t.co/gn6hrKsIXb

I’m using this post in my 4 PM VLM3D talk — just a quick reminder that social media captions are not always related to the images 😄

Starting at 11:45 AM in Room 306A — I’ll share how synthetic data can revolutionize dataset curation, annotation, and small-tumor detection, while improving AI generalization across cancers. See slides here https://t.co/zP3bMDROJd

Welcome to join my talk today in the CVAMD workshop! Here are the slides for preview: https://t.co/ws7TbWtz2X

Very much excited to give keynote at three #ICCV2025 workshops (finally in person this time, Zongweiiiiii in Hawaiiiiii) Oct 19, 13:25-13:50 Room 314, CVAMD Workshop Early Cancer Detection by Computed Tomography and Artificial Intelligence Oct 20, 11:45-12:20 Room 315, APAH

4 lines of code, the dataset is ready to use. #NeurIPS2025

Congrats Pedro ! #MICCAI2025 Best Paper Award runner-up.

A demo is fully available on GitHub https://t.co/yzsQ84oeS5 using public datasets PanTS (10K CT + Masks, JHU) and Merlin (25K CT + Reports, Stanford).

We are excited to introduce R-Super (Report Supervision), a new AI training method that learns tumor segmentation from radiology reports. This work has been short-listed for #MICCAI2025 Best Paper and Young Scientist Awards. @MICCAI_Society If you are in Korea, please visit

🧵 What if two images have the same local parts but represent different global shapes purely through part arrangement? Humans can spot the difference instantly! The question is can vision models do the same? 1/15

smarty-PanTS got accepted to ⁦@NeurIPSConf⁩

Join us for the first CS seminar of the semester with our very own @Zongwei_Zhou! Learn more here: https://t.co/avDUcYBkRR

The Cancer AI Alliance @CAIAorg, a partnership that includes @JohnsHopkins researchers like @alexisjbattle who are developing #AI-powered #cancer care, has been named to @TIME’s TIME100 AI 2025 list—learn more: https://t.co/NIj5TFuTLU

#HopkinsDSAI welcomes 22 new faculty members, who join more than 150 DSAI faculty members across @JohnsHopkins in advancing the study of data science, machine learning, and #AI and translation to a range of critical and emerging fields. https://t.co/tAauSzRFWD

a recipe to reproduce #Genie3: 1️⃣ collect a large egocentric video dataset and apply VGGT to get camera poses. Add more data from 3D reconstructed scenes. 2️⃣ train a Navigation World Model with long context → https://t.co/c3t8rnhdqX 3️⃣ distill to an efficient model for RT.