Over the last decade, the nanomedicine has experienced unprecedented development in
diagnosis and management of diseases. A number of nanomedicines have been approved …

The rapid development of precision medicine in recent years has started to challenge
diagnostic pathology with respect to its ability to analyze histological images and …

Quantitative evaluation of tissue images is crucial for computational pathology (CPath) tasks,
requiring the objective characterization of histopathological entities from whole-slide images …

The accelerated adoption of digital pathology and advances in deep learning have enabled
the development of robust models for various pathology tasks across a diverse array of …

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

Multimodal machine learning is a vibrant multi-disciplinary research field that aims to design
computer agents with intelligent capabilities such as understanding, reasoning, and learning …

Advances in digitizing tissue slides and the fast-paced progress in artificial intelligence,
including deep learning, have boosted the field of computational pathology. This field holds …

There have been hundreds of millions of cases of coronavirus disease 2019 (COVID-19),
which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). With …

Background Clinicians consider both imaging and nonimaging data when diagnosing
diseases; however, current machine learning approaches primarily consider data from a …

The recent explosion of interest in multimodal applications has resulted in a wide selection
of datasets and methods for representing and integrating information from different …