Meeting ReportOncology, Basic Science Track
Predicting lung cancer recurrence in patients within two years of curative radiotherapy via a trained machine learning algorithm.
Mark Bryanton, Rima Pathak, Dan La Russa, Oliver Holmes, Ryan Gotfrit, Graham Cook, Robert MacRae, Peter Cross and Jason Pantarotto
Journal of Nuclear Medicine May 2017, 58 (supplement 1) 113;
Mark Bryanton
1Department of Medicine, Division of Nuclear Medicine The Ottawa Hospital Ottawa ON Canada
Rima Pathak
4Division of Radiation Oncology University of Ottawa Ottawa ON Canada
Dan La Russa
3Division of Medical Physics University of Ottawa Ottawa ON Canada
Oliver Holmes
4Division of Radiation Oncology University of Ottawa Ottawa ON Canada
Ryan Gotfrit
2Department of Undergraduate Medical Education University of Ottawa Ottawa ON Canada
Graham Cook
4Division of Radiation Oncology University of Ottawa Ottawa ON Canada
Robert MacRae
4Division of Radiation Oncology University of Ottawa Ottawa ON Canada
Peter Cross
4Division of Radiation Oncology University of Ottawa Ottawa ON Canada
Jason Pantarotto
4Division of Radiation Oncology University of Ottawa Ottawa ON Canada

Article Figures & Data
Tables
Table 1: Accuracy of the Two Year Cancer Recurrence Prediction
Actual Patient Outcome Predicted 2 Year Lung Cancer Recurrence? No Yes Patient No 26 6 Outcome Yes 4 9
In this issue
Journal of Nuclear Medicine
Vol. 58, Issue supplement 1
May 1, 2017
Predicting lung cancer recurrence in patients within two years of curative radiotherapy via a trained machine learning algorithm.
Mark Bryanton, Rima Pathak, Dan La Russa, Oliver Holmes, Ryan Gotfrit, Graham Cook, Robert MacRae, Peter Cross, Jason Pantarotto
Journal of Nuclear Medicine May 2017, 58 (supplement 1) 113;
Predicting lung cancer recurrence in patients within two years of curative radiotherapy via a trained machine learning algorithm.
Mark Bryanton, Rima Pathak, Dan La Russa, Oliver Holmes, Ryan Gotfrit, Graham Cook, Robert MacRae, Peter Cross, Jason Pantarotto
Journal of Nuclear Medicine May 2017, 58 (supplement 1) 113;
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