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Machine Learning Methods to Predict Lung Cancer Survival Using the Veterans Affairs Research Precision Oncology Data Commons
Nhan V. Do, Jaime C. Ramos, Nathanael R. Fillmore, Robert L. Grossman, Michael Fitzsimons, Danne C. Elbers, Frank Meng, Brett R. Johnson, Samuel Ajjarapu, Corri L. DeDomenico, Karen E. Pierce-Murray, Robert B. Hall, Andrew F. Do, Kelly Gaynor, Peter L. Elkin, Mary T. Brophy
1453
10.3233/SHTI190480
Research Article
Studies in Health Technology and Informatics
Volume 264: MEDINFO 2019: Health and Wellbeing e-Networks for All
Abstract

We completed a pilot study to guide the development of the VA Research Precision Oncology Data Commons infrastructure as a collaboration platform with the greater research community. Our results using a small subset of patients from the VA’s Precision Oncology Program demonstrate the feasibility of our data sharing platform to build predictive models for lung cancer survival using machine learning, as well as highlight the potential of target genome sequencing data.

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