Deep model reassembly
In this paper, we explore a novel knowledge-transfer task, termed as Deep Model
Reassembly (DeRy), for general-purpose model reuse. Given a collection of heterogeneous …
Reassembly (DeRy), for general-purpose model reuse. Given a collection of heterogeneous …
Covid-19 image data collection: Prospective predictions are the future
Across the world's coronavirus disease 2019 (COVID-19) hot spots, the need to streamline
patient diagnosis and management has become more pressing than ever. As one of the …
patient diagnosis and management has become more pressing than ever. As one of the …
Kiut: Knowledge-injected u-transformer for radiology report generation
Radiology report generation aims to automatically generate a clinically accurate and
coherent paragraph from the X-ray image, which could relieve radiologists from the heavy …
coherent paragraph from the X-ray image, which could relieve radiologists from the heavy …
A vision–language foundation model for the generation of realistic chest x-ray images
The paucity of high-quality medical imaging datasets could be mitigated by machine
learning models that generate compositionally diverse images that faithfully represent …
learning models that generate compositionally diverse images that faithfully represent …
Roentgen: vision-language foundation model for chest x-ray generation
Multimodal models trained on large natural image-text pair datasets have exhibited
astounding abilities in generating high-quality images. Medical imaging data is …
astounding abilities in generating high-quality images. Medical imaging data is …
[HTML][HTML] Predicting COVID-19 pneumonia severity on chest X-ray with deep learning
Methods Images from a public COVID-19 database were scored retrospectively by three
blinded experts in terms of the extent of lung involvement as well as the degree of opacity. A …
blinded experts in terms of the extent of lung involvement as well as the degree of opacity. A …
Integrated multimodal artificial intelligence framework for healthcare applications
Artificial intelligence (AI) systems hold great promise to improve healthcare over the next
decades. Specifically, AI systems leveraging multiple data sources and input modalities are …
decades. Specifically, AI systems leveraging multiple data sources and input modalities are …
An open-source framework for end-to-end analysis of electronic health record data
With progressive digitalization of healthcare systems worldwide, large-scale collection of
electronic health records (EHRs) has become commonplace. However, an extensible …
electronic health records (EHRs) has become commonplace. However, an extensible …
On the limits of cross-domain generalization in automated X-ray prediction
This large scale study focuses on quantifying what X-rays diagnostic prediction tasks
generalize well across multiple different datasets. We present evidence that the issue of …
generalize well across multiple different datasets. We present evidence that the issue of …
Medical image captioning via generative pretrained transformers
The proposed model for automatic clinical image caption generation combines the analysis
of radiological scans with structured patient information from the textual records. It uses two …
of radiological scans with structured patient information from the textual records. It uses two …