Joseph Bae

Image: Joseph BaeJoseph Bae

Education:

B.S. University of Southern California (2018)

M.S. University of Southern California (2018)

Current Position:

3rd Year MSTP

1st Year Graduate Student

Advisor:

Prateek Prasanna

Graduate Program:

BMI

Research Interest:

 I am most generally interested in computational and physical science approaches to studying diseases. My previous research involved translational work studying circulating tumor cells (CTCs) in cancer patients. I primarily focused on prostate cancer and examined the effects of anti-cancer drugs on genotypic and phenotypic diversity in the population of a patient’s CTCs. 

My current interests lie in the application of machine learning to medical imaging data. Recent projects have included deep learning and radiomic analysis of chest x-rays in COVID-19 and the use of artificial intelligence to study radiotherapy in cancer. During my training I hope to develop computational techniques to make use of clinical and medical imaging data to improve patient outcomes.  

Publications:

Cowan, C.; Bae, J.; Singh, G.; Khullar, R.; Shah, S.; Madan, N.; Prasanna, P. Evolution of Chest Radiograph Radiomics and Association with Respiratory and Inflammatory Parameters in COVID-19 Patients Undergoing Prone Ventilation: Preliminary Findings; International Society for Optics and Photonics, 2021; Vol. 11597, p 1159709.

Bae, J.; Kapse, S.; Singh, G.; Phatak, T.; Green, J.; Madan, N.; Prasanna, P. Predicting Mechanical Ventilation Requirement and Mortality in COVID-19 Using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study. In submission. arXiv:2007.08028 [cs, eess, q-bio] 2020.

Khullar, R.; Shah, S.; Singh, G.; Bae, J.; Gattu, R.; Jain, S.; Green, J.; Anandarangam, T.; Cohen, M.; Madan, N. Effects of Prone Ventilation on Oxygenation, Inflammation, and Lung Infiltrates in COVID-19 Related Acute Respiratory Distress Syndrome: A Retrospective Cohort Study. Journal of clinical medicine 2020, 9 (12), 4129.

Konwer, A.; Bae, J.; Singh, G.; Gattu, R.; Ali, S.; Green, J.; Phatak, T.; Gupta, A.; Chen, C.; Saltz, J.; Prasanna, P. Predicting COVID-19 Lung Infiltrate Progression on Chest Radiographs Using Spatio-Temporal LSTM Based Encoder-Decoder Network; 2021.