The influx of deep learning (DL) techniques into the field of survival analysis in recent years
has led to substantial methodological progress; for instance, learning from unstructured or …

Background ROC (receiver operating characteristic) curve analysis is well established for
assessing how well a marker is capable of discriminating between individuals who …

Background & Aims The Model for End-Stage Liver Disease (MELD) has been established
as a reliable indicator of short-term survival in patients with end-stage liver disease. The …

scikit-survival is an open-source Python package for time-to-event analysis fully compatible
with scikit-learn. It provides implementations of many popular machine learning techniques …

Importance The association of tumor-infiltrating lymphocyte (TIL) abundance in breast
cancer tissue with cancer recurrence and death in patients with early-stage triple-negative …

Purpose The aim of the current study was to conduct a pooled analysis of studies that have
investigated the prognostic value of tumor-infiltrating lymphocytes (TILs) in early-stage triple …

Importance In patients with cancer who have venous thromboembolism (VTE) events, long-
term anticoagulation with low-molecular-weight heparin (LMWH) is recommended to prevent …

Background & Aims Non-invasive scoring systems (NSS) are used to identify patients with
non-alcoholic fatty liver disease (NAFLD) who are at risk of advanced fibrosis, but their …

Progression of nonalcoholic steatohepatitis (NASH) is incompletely characterized. We
analyzed data on longitudinal changes in liver histology, hepatic venous pressure gradient …

Risk prediction models need thorough validation to assess their performance. Validation of
models for survival outcomes poses challenges due to the censoring of observations and …