2022

• Kim, Doyun, Joowon Chung, Jongmun Choi, Marc D. Succi, John Conklin, Maria Gabriela Figueiro Longo, Jeanne B. Ackman, Brent P. Little, Milena Petranovic, Mannudeep K. Kalra, Michael H. Lev, and Synho Do. “Accurate auto-labeling of chest X-ray images based on quantitative similarity to an explainable AI model.” Nature Communications 13, no. 1 (2022): 1867.
• Jongmun Choi, , Soomin Jeon, Doyun Kim, Michelle Chua, and Synho Do. “A scalable artificial intelligence platform that automatically finds copy number variations (CNVs) in journal articles and transforms them into a database: CNV extraction, transformation, and loading AI (CNV-ETLAI)”.Computers in Biology and Medicine 144 (2022): 105332.
• Zhang, Mingjuan L., Jongmun Choi, Richard Judelson, Soomin Jeon, Deepa Patil, Vikram Deshpande, and Synho Do. “Small and Efficient Artificial Intelligence Model Can Differentiate Hyperplastic Polyps and Sessile Serrated Adenomas/Polyps.” Gastroenterology 162 (7): S701-S701 (2022).
• Joowon Chung, Doyun Kim, Jongmun Choi, Sehyo Yune, Kyoung Doo Song, Seonkyoung Kim, Michelle Chua, Marc D. Succi, John Conklin, Maria G. Figueiro Longo, Jeanne B. Ackman, Milena Petranovic, Michael H. Lev and Synho Do. “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”. Sci Rep12, 21164 (2022).
• Michelle Chua, Doyun Kim, Jongmun Choi, Michael H. Lev, Ramon G. Gonzalez, Michael S. Gee and Synho Do. “Tackling prediction uncertainty in machine learning for healthcare”. Nat. Biomed. Eng 7, 711–718 (2023).