The COVID-19 global pandemic is a threat not only to the health of millions of individuals,
but also to the stability of infrastructure and economies around the world. The disease will …

In current research, emotions in language use situations are often examined only at their
starting and ending points, akin to observing the beginning and end of a wave, while …

Glioblastoma (GBM) is a common malignant brain tumor which often presents as a
comorbidity with central nervous system (CNS) disorders. Both CNS disorders and GBM …

Cold-start diagnosis prediction is a challenging task for AI in healthcare, where often only a
few visits per patient and a few observations per disease can be exploited. Although meta …

Artificial intelligence is constantly revolutionizing biomedical research and healthcare
management. Disease comorbidity is a major threat to the quality of life for susceptible …

The discovery of structure from time series data is a key problem in fields of study working
with complex systems. Most identifiability results and learning algorithms assume the …

For centuries, scientists have manually designed closed-form ordinary differential equations
(ODEs) to model dynamical systems. An automated tool to distill closedform ODEs from …

In recent years, marked temporal point processes (MTPPs) have emerged as a powerful
modeling machinery to characterize asynchronous events in a wide variety of applications …

Background and objective: Using graph theory, Electronic Health Records (EHRs) can be
represented graphically to exploit the relational dependencies of the multiple information …

We propose a modeling framework for event data and aim to answer questions such
as\emph {when} and\emph {why} the next event would happen. Our proposed model excels …