In this paper, we propose a novel Prediction Model to Study the Impact of Lymphopenia Kinetics on Survival Outcomes in HNSCC Via an Ensemble Tree-Based Machine Learning Approach (POTOMAC). Our main ...

PURPOSEThere is limited knowledge of the prediction of 2-year cancer-specific survival (CSS) in the head and neck cancer (HNC) population. The aim of this study is to develop and validate machine ...

Decision Tree and Random Forest Decision trees are used in many types of machine learning problems including multi-class classification.

A new study leveraged machine learning (ML) to predict 5-year postoperative survival in patients with stage III colorectal cancer (CRC), identifying key clinical and demographic factors that ...

The machine learning model had better performance than the conventional models and the random forest model best predicted the short-term survival of ACLF patients following liver transplant.

Blood samples collected from patients with severe COVID-19 can be analyzed by a machine learning approach to predict whether they will recover and survive or die from the disease, a PLOS Digital ...

The machine learning algorithms were developed and tested on nearly 10,000 cases of OHCA that happened in Chicago's 77 neighborhoods between 2014 and 2019.