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

Due to the inherent flexibility of prompting, foundation models have emerged as the
predominant force in the fields of natural language processing and computer vision. The …

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 …

The advent of foundation models (FMs) as an emerging suite of AI techniques has struck a
wave of opportunities in computational healthcare. The interactive nature of these models …

The deep learning field is converging towards the use of general foundation models that can
be easily adapted for diverse tasks. While this paradigm shift has become common practice …

Due to the flexibility of prompting, foundation models have become the dominant force in the
domains of natural language processing and image generation. With the recent introduction …

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 …

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 …

Companion robots are aimed to mitigate loneliness and social isolation among older adults
by providing social and emotional support in their everyday lives. However, older adults' …

The conventional pretraining-and-finetuning paradigm, while effective for common diseases
with ample data, faces challenges in diagnosing data-scarce occupational diseases like …