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 ...

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 ...

Next, the researchers developed a “survival tree” machine-learning model which allowed them to build a prognostic model by adding in different variables. In prognostic modeling, the greatest increase ...

A single blood sample from a critically ill COVID-19 patient can be analyzed by a machine learning model which uses blood plasma proteins to predict survival, weeks before the outcome, according ...

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 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.

The team then developed a machine learning model to predict survival based on a single time-point measurement of relevant proteins and tested the model on an independent validation cohort of 24 ...

A UCLA-led team has developed a machine-learning model that can predict with a high degree of accuracy the short-term survival of dialysis patients on Continuous Renal Replacement Therapy (CRRT).