Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …

With the development of digital pathology and the renewal of deep learning algorithm,
artificial intelligence (AI) is widely applied in tumor pathology. Previous researches have …

Healthcare data are inherently multimodal, including electronic health records (EHR),
medical images, and multi-omics data. Combining these multimodal data sources …

Cancer diagnosis and treatment decisions often focus on one data source. Steyaert and
colleagues discuss the current status and challenges of data fusion, including electronic …

Herbicides and heavy metals are hazardous substances of environmental pollution,
resulting in plant stress and harming humans and animals. Identification of stress types can …

The rapid development of diagnostic technologies in healthcare is leading to higher
requirements for physicians to handle and integrate the heterogeneous, yet complementary …

Current methods for analyzing single-cell datasets have relied primarily on static gene
expression measurements to characterize the molecular state of individual cells. However …

Multi-omics technologies are being increasingly utilized in angiogenesis research. Yet,
computational methods have not been widely used for angiogenic target discovery and …

Objective Alzheimer's disease (AD) is the most common neurodegenerative disorder with
one of the most complex pathogeneses, making effective and clinically actionable decision …

Lung cancer accounts for more deaths worldwide than any other cancer disease. In order to
provide patients with the most effective treatment for these aggressive tumours, multimodal …