Machine Learning Classifier to Reproduce Lung Metastases Tumor Board Decisions

This study demonstrates that relatively simple variables taken from patient records can be used to create a model that generates recommendations concordant with an MDT. The next steps of the study include extracting and processing cross-sectional imaging to acquire exact tumor dimensions, density and location with respect to the pleura, fissures, bronchi, and vessels. This may improve the current classifier performance, as well as allow for more detailed predictions such as further classifying local treatment decisions into surgery and SBRT.