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Great advice for radiology trainees:: Preparing Radiologists for an Artificial Intelligence–enhanced Future: Tips for Trainees | RadioGraphics pubs.rsna.org/doi/10.1148/rg…

Excited to introduce RadGraph2: A new dataset for tracking disease progression in radiology reports! 🏥📊 Key features: 800 expert-annotated reports 220k+ machine-labeled reports Captures changes in:Disease onset, progression, improvement & resolution Medical device placement &

Thanks!! AK 🚨📷🚨 Excited to share our new work "MedTrinity-25M: A Large-scale Multimodal Dataset with Multigranular Annotations for Medicine" Paper: arxiv.org/abs/2408.02900 Dataset: huggingface.co/datasets/UCSC-… Code & models: github.com/UCSC-VLAA/MedT… Highlights: 👉 A

⭐️ Announcing ReXRank, a competition for radiology report generation from Chest X-Rays. Featuring 16 existing competitive approaches, a large private test leaderboard of 10k cases indicative of more real-world performance, and a live arena where radiology experts can do a

Cancer in the young is on the rise worldwide, but the basis for this is not known. A new review covers it well, open-access cell.com/cell-reports-m… Alberto Bardelli @GianMau1990 Cell Reports Medicine

Are you a radiologist interested in shaping the future of AI in healthcare? At Rajpurkar Lab, we are looking for collaborators to join us in an exciting upcoming project. If interested, please reach out - DMs are open! Pranav Rajpurkar

Arguably one of the most underrated skills in academic research (esp in CS/ML/AI world) is to create captivating visuals, see eg 👇

We are transitioning from CXR to CT reporting!

Looking forward to it. We’re at an inflection point for radiology Ai, and in my talk, I’ll make the case for the emerging generalist medical ai paradigm and how that will change the kinds of AI models we will deploy for radiologists in the future.

AI models should be clinically validated to demonstrate benefit and implement effectively! Our clinical trial of AI-assisted contouring for breast radiation therapy is a case in point, showing no efficiency improvements despite promising pre-clinical evidence. Ray Mak, MD #ASTRO24

At least 50% of the variance in common diseases is due to environmental exposures. NEXUS is a first step to the Human Exposome Project that is essential to understanding and preventing disease.

🚀 Catching Misses by Doctors! 🚀 a2z-1 launches: AI tackling one of the most common radiological exams - abdominal-pelvis CT scans. 21 conditions. One AI. Unlimited potential. And it's just the beginning. Ever wondered the vision and story behind? 👇 a2zradiology.ai/news/a2z-radio…

Can Anthropic Claude 3.5 sonnet outperform OpenAI o1 in reasoning? Combining Dynamic Chain of Thoughts, reflection, and verbal reinforcement, existing LLMs like Claude 3.5 Sonnet can be prompted to increase test-time compute and match reasoning strong models like OpenAI o1.

Healthcare feels like a top 3 place to build over the next decade. -- $4.5T US spend//20% of GDP --> huge market -- up to 25% of the world's data is healthcare related --> huge data set --> big surface area to build -- not available on the public internet --> not in

I'm excited to let you know I have a new book coming out next spring. amazon.com/Super-Agers-Ev… Simon & Schuster

MRI saved my life. It may save yours too. I’m excited to announce the world's best full-body MRI protocol in partnership with Ezra®. This Blueprint MRI includes everything I’ve learned over the past four years becoming the most MRI-measured person in the world. This is me👇

It's no trick! 🎃 Join us 10/31 for the CPH fall seminar series on medical #AI: Pranav Rajpurkar PhD presents on "Human-AI Interaction in Radiology." Thu, Oct. 31, 10-11 AM PDT Register here: buff.ly/3YgP5oS

A pleasure to collaborate with Jung-Oh Lee, Hong-Yu Zhou, Tyler Berzin MD, FASGE, Daniel Sodickson on rethinking the frontier of multimodal generative ai for complex medical data!