MIRA Clinical Learning Environment (MIRACLE): Lung

The goal of this quality improvement (QI) study is to develop automated clinical pipelines to implement machine learning models in the care pathway of lung cancer patients. The main questions it aims to answer are:Can model-prompted risk classifications be incorporated into clinician workflows to enable informed clinical decision-making?What are clinicians' perceptions of the information from model outputs, and do they change their decision about data already available to them as a result of the model-prompted risk classification (i.e., to re-review or further assess patients identified by the models as being higher risk)?Participating radiation oncologists will receive the risk prediction from the model and be asked to complete a survey to give feedback on how they used the prediction in their decision-making.

Inclusion Criteria:Diagnosed with lung cancer stage I-IV and planned for treatment with radiotherapy at Princess Margaret hospital. The three aims of this project have specific inclusion criteria as follows.Aim 1 ILD: All lung cancer patients receiving RT.Aim 2 SGR: Node negative lung cancer patients receiving stereotactic body RT.Aim 3 CBCT: Node positive lung cancer patients receiving standard RT.Exclusion Criteria:No exclusion criteria