Author: McKell Woodland

Awarded a snap oral presentation at AAPM’s annual meeting. The title of the presentation will be “Interpretable Out-of-Distribution Detection with Generative Adversarial Networks”.

Lead instructor for an “Introduction to Machine Learning” course through the Coding School and sponsored by Amazon Web Services. Course is being taught to 50 HBCU and community college professors.

Diagnostics | Automated Contouring and Planning in Radiation Therapy: What Is ‘Clinically Acceptable’? (mdpi.com)

Comparison of Machine Learning and Deep Learning Methods for the Prediction of Osteoradionecrosis Resulting from Head and Neck Cancer Radiation Therapy – International Journal of Radiation Oncology, Biology, Physics (redjournal.org)

StyleGAN2-based Out-of-Distribution Detection for Medical Imaging

extended abstract

Volunteering through the TRAIN initiative to teach machine learning to 40 high school students across the United States.

Woodland, M. et al. (2022). Evaluating the Performance of StyleGAN2-ADA on Medical Images. In: Zhao, C., Svoboda, D., Wolterink, J.M., Escobar, M. (eds) Simulation and Synthesis in Medical Imaging. SASHIMI 2022. Lecture Notes in Computer Science, vol 13570. Springer, Cham. https://doi.org/10.1007/978-3-031-16980-9_14

Paper entitled “Evaluating the performance of StyleGAN2-ADA on Medical Images” to be published in the conference proceedings of the SASHIMI (Simulation and Synthesis in Medical Imaging) workshop as part of the 2022 MICCAI conference. Workshop will be held on September 18th in Singapore.

Became a member of The Coding School‘s Young Professional Advisory Board. I will specifically be giving guidance on the AI curriculum development for the TRAIN grant.