2023

• Chung, J., Kim, D., Choi, J., Yune, S., Song, K. D., Kim, S., Chua, M., Succi, M. D., Conklin, J., Longo, M. G. F., Ackman, J. B., Petranovic, M., Lev, M. H., & Do, S. “Prediction of oxygen requirement in patients with COVID-19 using a pre-trained chest radiograph xAI model: efficient development of auditable risk prediction models via a fine-tuning approach”. Scientific reports, 13(1), 4296 (2023).
• Yoon, Byung C., Pomerantz, Stuart R., Mercaldo, Nathaniel D., Goyal, Swati, L’Italien, Eric M., Lev, Michael H., Buch, Karen A., Buchbinder, Bradley R., Chen, John W., Conklin, John, Gupta, Rajiv AND Hunter, George J., Kamalian, Shahmir C., Kelly, Hillary R., Rapalino, Otto, Rincon, Sandra P., Romero, Javier M., He, Julian, Schaefer, Pamela W., Do, Synho, González, Ramon. “Incorporating algorithmic uncertainty into a clinical machine deep learning algorithm for urgent head CTs”.PLOS ONE 18, no.3 (2023): 1-15.
• Bahl, Manisha, and Synho, Do. “Beyond the AJR: An International Competition Advances Artificial Intelligence Research”.AJR. American journal of roentgenology (2023).
• Bahl, Manisha, and Synho, Do. “Artificial Intelligence Applied to Contrast-enhanced Mammography: Exploring Uncharted Territory”.Radiology 307, no.5 (2023): e231140.