This article discusses the opportunities, applications and future directions of large-scale
pretrained models, ie, foundation models, which promise to significantly improve the …

Foundation model, which is pre-trained on broad data and is able to adapt to a wide range
of tasks, is advancing healthcare. It promotes the development of healthcare artificial …

The integration of Computer-Aided Diagnosis (CAD) with Large Language Models (LLMs)
presents a promising frontier in clinical applications, notably in automating diagnostic …

Inadequate generality across different organs and tasks constrains the application of
ultrasound (US) image analysis methods in smart healthcare. Building a universal US …

Overcoming barriers on the use of multi-center data for medical analytics is challenging due
to privacy protection and data heterogeneity in the healthcare system. In this study, we …

The emerging trend of advancing generalist artificial intelligence, such as GPTv4 and
Gemini, has reshaped the landscape of research (academia and industry) in machine …

The increasing use of medical imaging in healthcare settings presents a significant
challenge due to the increasing workload for radiologists, yet it also offers opportunity for …

Radiation therapy is a primary and effective NasoPharyngeal Carcinoma (NPC) treatment
strategy. The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk …

Recently, large pretrained vision foundation models based on masked image modeling
(MIM) have attracted unprecedented attention and achieved remarkable performance across …

Foundation models pre-trained on large-scale data have been widely witnessed to achieve
success in various natural imaging downstream tasks. Parameter-efficient fine-tuning (PEFT) …