Zhihong Chen

Today, @zhjohnchan, @Dr_ASChaudhari and I introduce Cognita. Over half the world lacks access to sufficient healthcare. We started Cognita a year ago to address this. Radiology is (1) the first-line diagnostic specialty, (2) facing a worsening workforce shortage, and (3) highly digitized, enabling AI to have an enormous impact. Stage 1 of our company is focused on increasing the world’s access to radiology. To do this, we are building models that emulate radiologists - describing in detail hundreds of potential imaging findings and comparing to prior studies. This is a departure from existing narrow radiology AI solutions that only provide a yes/no answer for a specific finding. Our goal is to build copilots that help radiologists perform more accurately, efficiently, and with higher satisfaction, leading to reduced missed diagnoses and shortened patient wait times. We partnered with @Rad_Partners from day 1 to make this vision a reality. This collaboration has given us access to the required scale of data, and a hand-in-hand partnership with radiologists who have more experience validating and deploying radiology models than any other team on the planet. What our teams have accomplished together over the past year is extraordinary, seeing unprecedented performance across X-ray and CT. Stage 2 will focus on adding diagnostic capabilities that extend beyond current radiology practice, such as risk prediction and quantification across time. Stage 3 will incorporate additional data types - clinical notes, medical records, labs, omics, pathology - to deliver improved diagnostics and personalized treatment recommendations. Because our partnership has been so compelling over the past year, we decided to fully join forces with Mosaic Clinical Technologies, @Rad_Partners' technology division, through an acquisition. This creates further alignment, and is carefully structured to increase Cognita’s velocity. We strongly believe this is the right path forward to increase the world’s access to healthcare. We are just getting started and the future of healthcare AI is incredibly exciting. If you’re motivated to engineer solutions to one of the most challenging technical problems and impact patient lives every day, there is no better place to be. Please consider applying at jobs.ashbyhq.com/cognita-imaging.

arXiv -> alphaXiv Students at Stanford have built alphaXiv, an open discussion forum for arXiv papers. @askalphaxiv You can post questions and comments directly on top of any arXiv paper by changing arXiv to alphaXiv in any URL!

🧙 Excited to introduce Merlin, a vision language foundation model for 3D computed tomography 🐈‍⬛🩻 Trained to understand 3D abdominal CT scans using supervision from: 💾 Structured electronic health records (1.8+ million codes) 🗒️ Natural language radiology reports (6+ million tokens) Paper: arxiv.org/abs/2406.06512 🧵 1/10

Five years ago, thanks to the leadership of @mattlungrenMD, @stanfordAIMI released the CheXpert images: 223K JPG CXRs with labels for 14 conditions. CheXpert has been cited >6000 times, mostly related to development of supervised learning methods. Much has changed since then.🧵