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Found 3 papers, 1 papers with code
A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics
This shift encompasses a move from discriminative AI approaches to generative AI approaches, as well as a shift from model-centered methodologies to datacentered methodologies.
P-Transformer: A Prompt-based Multimodal Transformer Architecture For Medical Tabular Data
While deep learning approaches, particularly transformer-based models, have shown remarkable performance in tabular data prediction, there are still problems remained for existing work to be effectively adapted into medical domain, such as under-utilization of unstructured free-texts, limited exploration of textual information in structured data, and data corruption.
UFRC: A Unified Framework for Reliable COVID-19 Detection on Crowdsourced Cough Audio
We suggested a unified system with core components of data augmentation, ImageNet-pretrained ResNet-50, cost-sensitive loss, deep ensemble learning, and uncertainty estimation to quickly and consistently detect COVID-19 using acoustic evidence.
