Survival analysis is a subfield of statistics where the goal is to analyze and model data
where the outcome is the time until an event of interest occurs. One of the main challenges …

Medical data refers to health-related information associated with regular patient care or as
part of a clinical trial program. There are many categories of such data, such as clinical …

In medicine, survival analysis studies the time duration to events of interest such as mortality.
One major challenge is how to deal with multiple competing events (eg, multiple disease …

Survival analyses of populations and the establishment of prognoses for individual patients
are important activities in the practice of medicine. Standard survival models, such as the …

Motivation Recent advances in deep learning have offered solutions to many biomedical
tasks. However, there remains a challenge in applying deep learning to survival analysis …

RNA sequencing has emerged as a promising approach in cancer prognosis as sequencing
data becomes more easily and affordably accessible. However, it remains challenging to …

Online donation-based crowdfunding has brought new life to charity by soliciting small
monetary contributions from crowd donors to help others in trouble or with dreams. However …

Background Gene expression plays a key intermediate role in linking molecular features at
the DNA level and phenotype. However, owing to various limitations in experiments, the …

Least squares estimators, when trained on few target domain samples, may predict poorly.
Supervised domain adaptation aims to improve the predictive accuracy by exploiting …

In the current information era, we rely on cyber techniques and principles to protect the
confidentiality, integrity, and availability of everything from personally identifiable information …