Worrying if my job was jeopardized by AI this week or if we’re still good, I read a new paper evaluating #GPT4V - a #GPT4 version handling image and text inputs. It produces *impressive* radiology reports. But let’s delve deeper into some of the results... #radiology #AI Here, GPT4V correctly identified a fracture of the 5th metatarsal bone. However, this is not a Jones fracture (which is in the proximal part of the bone and sometimes doesn’t heal well, requiring more aggressive management). Almost correct ≠ Correct, esp. in medicine.

🎉Introducing RoentGen, a generative vision-language foundation model based on #StableDiffusion, fine-tuned on a large chest x-ray and radiology report dataset, and controllable through text prompts!

@PierreChambon6 @Dr_ASChaudhari @curtlanglotz

🧵#Radiology #AI #StanfordAIMI #RoentGen is able to generate a wide variety of radiological chest x-ray (CXR) findings with fidelity and high level of detail. Of note, this is without being explicitly trained on class labels.

🎉 #StableDiffusion can be fine-tuned to generate medical images, and the outputs can be controlled using natural language text prompts!

In our latest work, we use SD to create synthetic chest xrays and insert pathologies like pleural effusions.

🧵 #Radiology #AI #StanfordAIMI #stablediffusion is a #LatentDiffusionModel and performs its generative tasks efficiently on low-dimensional representations of high-dimensional training inputs. SD's VAE latent space preserves relevant information contained in CXR; they can be reconstructed with high fidelity.