AI-powered
podcast player
Listen to all your favourite podcasts with AI-powered features
Training a Model for Aligning Vision Encoders with Language Encoders in Medical Contexts
This chapter explores the architecture and training process of a model that aligns vision and language encoders in the context of medical texts and images. It discusses the use of off-the-shelf architectures, fine-tuning on pathology images and text descriptions, and the benefits of broader pre-training for improving conversational capabilities. It also touches on the challenges and dangers of using practitioner models, the potential of leveraging public data, and the importance of quantitative evaluation.