Abstract Cox Proportional Hazards (CPH) analysis is the standard for survival analysis in
oncology. Recently, several machine learning (ML) techniques have been adapted for this …

Abstract Nowadays Artificial Intelligence (AI) has become a fundamental component of
healthcare applications, both clinical and remote, but the best performing AI systems are …

As a highly contagious respiratory disease, COVID-19 has yielded high mortality rates since
its emergence in December 2019. As the number of COVID-19 cases soars in epicenters …

Abstract Background and Objective: Survival prediction of heart failure patients is critical to
improve the prognostic management of the cardiovascular disease. The existing survival …

Tumor gene expression is predictive of patient prognosis in some cancers. However, RNA-
seq and whole genome sequencing data contain not only reads from host tumor and normal …

The COVID-19 pandemic overwhelms the medical resources in the stressed intensive care
unit (ICU) capacity and the shortage of mechanical ventilation (MV). We performed CT …

Objective By using machine learning, our study aimed to build a model to predict risk and
time to total knee replacement (TKR) of an osteoarthritic knee. Methods Features were from …

A weighted random survival forest is presented in the paper. It can be regarded as a
modification of the random forest improving its performance. The main idea underlying the …

As portable chest X-rays are an efficient means of triaging emergent cases, their use has
raised the question as to whether imaging carries additional prognostic utility for survival …

Purposes and Objectives The aim of this study was to predict the progression-free survival
(PFS) in patients with small cell lung cancer (SCLC) by radiomic signature from the contrast …