Fantastic co-authors including co-first author Jaehwan Jeong, with Benjamin Tran, Daniel Schlessinger, Shannon Wongvibulsin, Leandra Barnes, Hong-Yu Zhou, Zhuo Ran Cai, Eli Van Allen, and David Kim.

A big congratulations to star Harvard PhD student Shreya Johri, and what a delight to co-lead this work with
@roxanadaneshjou.bsky.social.

Read our paper here: rdcu.be/d5ovt

I encourage academic and commercial groups to join in the competition and showcase the best you have:
rexrank.ai

If developers are coming to you with a model claiming to perform great report generation on chest X-rays, ask them to do a fair comparison on ReXrank. Let's separate the hype from the reality.

We have now launched a competition called ReXrank to track progress.
With Gradient Health, we have collaborated to produce the now the largest and cleanest private dataset to evaluate models.

Medical Image Interpretation course page: onlinelearning.hms.harvard.edu/hmx/hmx-pro/...
Biomedical Signal Interpretation course page: onlinelearning.hms.harvard.edu/hmx/hmx-pro/...

Includes a cameo by @mattlungrenmd.bsky.social , as the course covers an expert perspective on real-world AI in radiology.

Most importantly, it's curated to be very accessible and approachable, requiring no mathematical background. I walk you through the science. And it's short :) Here's a teaser for one of the courses – this is on Medical Image Interpretation.

I've curated lessons using real-world research examples, where I go through classic problem formulations and how they have been approached by world-class teams. For some case studies, I've used examples from my own research to give you insight into the back story surrounding cutting-edge research.