Technological advances have made it possible to study a patient from multiple angles with
high-dimensional, high-throughput multiscale biomedical data. In oncology, massive …

Salient object detection, which simulates human visual perception in locating the most
significant object (s) in a scene, has been widely applied to various computer vision tasks …

Background An increase in lifespan in our society is a double-edged sword that entails a
growing number of patients with neurocognitive disorders, Alzheimer's disease being the …

Incomplete multi-view clustering aims to exploit the information of multiple incomplete views
to partition data into their clusters. Existing methods only utilize the pair-wise sample …

Detecting and segmenting salient objects from natural scenes, often referred to as salient
object detection, has attracted great interest in computer vision. While many models have …

With the fast progress in information technologies and artificial intelligence (AI), smart
healthcare has gained considerable momentum. By using advanced technologies like AI …

The automatic diagnosis of various retinal diseases from fundus images is important to
support clinical decision-making. However, developing such automatic solutions is …

Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …

With the advance of medical imaging technologies, multimodal images such as magnetic
resonance images (MRI) and positron emission tomography (PET) can capture subtle …

Multi-view clustering aims to cluster data from diverse sources or domains, which has drawn
considerable attention in recent years. In this paper, we propose a novel multi-view …