Nature

Machine learning survival models trained on clinical data to identify high risk patients with hormone responsive HER2 negative breast cancer

For endocrine-positive Her2 negative breast cancer patients at an early stage, the benefit of adding chemotherapy to adjuvant endocrine therapy is not still confirmed. Several genomic tests are ...
Nature

Survival machine learning models for predicting all-cause and case-specific mortality risk in metabolic dysfunction-associated fatty liver disease patients

Emerging evidence links metabolic dysfunction-associated fatty liver disease (MAFLD) with increased all-cause and circulatory system disease (CSD) mortality in adults, yet survival machine learning ...

Diet remodels chromatin structure and extends survival in models of glioma

An unexpected lab observation has led a team of scientists to discover how diet can influence survival in animal models of ...
ascopubs.org

SOURCE beyond first-line: A survival prediction model for patients with metastatic esophagogastric adenocarcinoma after failure of first-line palliative systemic therapy.

The PRODIGE 59-DURIGAST trial: A randomized phase II study evaluating FOLFIRI plus durvalumab and FOLFIRI plus durvalumab plus tremelimumab in second-line treatment of patients with advanced gastric ...
ascopubs.org

Interactive Use of Cox Model–Predicted Survival Curves: An Application Using ACS10 Score and Age to Personalize Treatment of Pediatric AML

Timing of Adjuvant Chemotherapy After Gastrectomy in Patients With Stage II to III Gastric Cancer: A Target Trial Emulation Study We created a publicly available software library, shinyCox, that can ...