Understanding New Machine Learning Architectures: Practical Generative Artificial Intelligence for Anesthesiologists.

ABSTRACT: Recent advances in neural networks have given rise to generative artificial intelligence, systems able to produce fluent responses to natural questions or attractive and even photorealistic images from text prompts. These systems were developed through new network architectures that permit massive computational resources to be applied efficiently to enormous data sets. First, this review examines autoencoder architecture and its derivatives the variational autoencoder and the U-Net in annotating and manipulating images and extracting salience. This architecture will be important for applications like automated x-ray interpretation or real-time highlighting of anatomy in ultrasound images. Second, this article examines the transformer architecture in the interpretation and generation of nat

SUBMITTER: Connor CW 

PROVIDER: S-EPMC10868863 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature