CLL-TIM Treatment and Infection Modelling for Chronic Lymphocytic Leukemia

CLL Treatment and Infection Modelling (CLL-TIM) is a model for predicting risk of infection or CLL treatment within the next 2-years. CLL-TIM is trained on a Danish dataset of 4149 patients diagnosed with CLL in the period of 2004-2017. The prediction of 28 machine-learning algorithms is combined into a single prediction using ensemble modelling. With CLL-TIM you are provided with

• A prediction of whether a patient is at a high or low-risk of infection or treatment within the next 2 years.
• A confidence score indicating the reliability of CLL-TIM’s prediction.
• A set of patient specific risk factors that were responsible in driving the patient towards the given risk.

CLL-TIM Prediction Options

• 1. Predict using CLL-TIM User-Interface

• 2. Predict Using CLL-TIM Data Upload

Download Example Templates to be used with Prediction Option 2

• CLL-TIM Data Input Format

• CLL-TIM High Risk Patient Example 1

• CLL-TIM High Risk Patient Example 2

• CLL-TIM High Risk Patient Example 3

• CLL-TIM Low Risk Patient Example 1

• CLL-TIM Low Risk Patient Example 2

• CLL-TIM Low Risk Patient Example 3