Large ai models in health informatics: Applications, challenges, and the future
Large AI models, or foundation models, are models recently emerging with massive scales
both parameter-wise and data-wise, the magnitudes of which can reach beyond billions …
both parameter-wise and data-wise, the magnitudes of which can reach beyond billions …
Pre-trained language models in biomedical domain: A systematic survey
Pre-trained language models (PLMs) have been the de facto paradigm for most natural
language processing tasks. This also benefits the biomedical domain: researchers from …
language processing tasks. This also benefits the biomedical domain: researchers from …
ChatGPT and other large language models are double-edged swords
rules integrated into its technology. Additionally, users must carefully craft questions or
prompts, providing specific information about a clinical scenario and potential …
prompts, providing specific information about a clinical scenario and potential …
Extracting training data from diffusion models
Image diffusion models such as DALL-E 2, Imagen, and Stable Diffusion have attracted
significant attention due to their ability to generate high-quality synthetic images. In this work …
significant attention due to their ability to generate high-quality synthetic images. In this work …
Holistic evaluation of text-to-image models
The stunning qualitative improvement of text-to-image models has led to their widespread
attention and adoption. However, we lack a comprehensive quantitative understanding of …
attention and adoption. However, we lack a comprehensive quantitative understanding of …
Clip-driven universal model for organ segmentation and tumor detection
An increasing number of public datasets have shown a marked impact on automated organ
segmentation and tumor detection. However, due to the small size and partially labeled …
segmentation and tumor detection. However, due to the small size and partially labeled …
Prompt engineering for healthcare: Methodologies and applications
Prompt engineering is a critical technique in the field of natural language processing that
involves designing and optimizing the prompts used to input information into models, aiming …
involves designing and optimizing the prompts used to input information into models, aiming …
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 …
A pathway towards responsible ai generated content
AI Generated Content (AIGC) has received tremendous attention within the past few years,
with content generated in the format of image, text, audio, video, etc. Meanwhile, AIGC has …
with content generated in the format of image, text, audio, video, etc. Meanwhile, AIGC has …
Leaving reality to imagination: Robust classification via generated datasets
Recent research on robustness has revealed significant performance gaps between neural
image classifiers trained on datasets that are similar to the test set, and those that are from a …
image classifiers trained on datasets that are similar to the test set, and those that are from a …