Multimodal biomedical AI

By J. Acosta, G. Falcone, Pranav Rajpurkar, Eric J. Topol. Nature Medicine, 2022

1,074 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Health Informatics, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/dda118e8154765f73cb8f5e2b1b8daa75faf726f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Stefan Harrer

In Health Informatics

1. Stefan Harrer

In Radiology, Nuclear Medicine and Imaging

1. Stefan Harrer

Citations in the corpus

• Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine (2023, background): “…will run into the ‘ big data ’ problem, i.e., will have to face the fact that while theoretically electronic health records are a multimodal bottomless ocean of big data poised to be analysed using deep learning models, 74 when it comes to getting access to such data, they very much are not.”