Sunan Cui, PhD
Sunan Cui received her B.S. in physics from University of Science and Technology of China (USTC) in 2015. She simultaneously obtained her PhD in applied physics and M.A. in Statistics from University of Michigan - Ann Arbor in 2020. Her PhD work, supported by NCI, Rackham predoctoral fellowship, Applied Physics fellowship at University of Michigan, focused on incorporating machine learning/deep learning techniques into outcome modeling for adaptive radiotherapy.
Sunan joined the Stanford Medical Physics Residency Program in 2020.
Cui, S., Tseng, H.‐H., Pakela, J., Ten Haken, R.K. and El Naqa, I. (2020), Introduction to machine and deep learning for medical physicists. Med. Phys., 47: e127-e147. doi:10.1002/mp.14140 Special Issue, Medical Physics
Cui, S., Luo, Y., Tseng, H.-H, Ten Haken, R.K. and El Naqa, I. (2019), Combining Handcrafted Features with Latent Variables in Machine Learning for Prediction of Radiation- Induced Lung Damage, Medical Physics, 46(5)
Cui, S., Luo, Y., Tseng, H.-H, Ten Haken, R.K. and El Naqa, I. (2019) “Artificial Neural Network With Composite Architectures for Prediction of Local Control in Radiotherapy, IEEE TRPMS, 3(2)
Cui, S., Ten Haken, R.K. and El Naqa, I, “Building a Predictive Model of Toxicity: Methods", in Rancati, Tiziana & Fiorino, Claudio (Eds), “Modelling Radiotherapy Side Effects: Practical Applications for Planning Optimization", CRC press, 2019.
Luo, Y., Tseng, H.-H, Cui, S., et al. “Balancing accuracy and interpretability of machine learning approaches for radiation treatment outcomes modeling", BJROpen 2019 1:1
Tseng, H.-H, Wei, L., Cui, S., et al. (2018) “ Machine Learning and Imaging Informatics in Oncology", Oncology, DOI/10.1159/000493575
Tseng, H.-H, Luo, Y., Cui, S., Chien, JT, Ten Haken, R.K., El Naqa, I. “Deep Reinforcement Learning for Automated Radiation Adaptation in Lung Cancer" (AAPM Farrington Daniels Award), Medical Physics; 2017 Dec; 44(12).