Joanna X. Liang

According to our database, Joanna X. Liang authored at least 3 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

AI-derived epicardial fat measurements improve cardiovascular risk prediction from myocardial perfusion imaging.

Robert J. H. Miller, Aakash D. Shanbhag, Aditya Killekar, Mark Lemley, Bryan P. Bednarski, Serge D. Van Kriekinge, Paul Kavanagh, Attila Feher, Edward J. Miller, Andrew J. Einstein, Terrence D. Ruddy, Joanna X. Liang, Valerie Builoff, Daniel S. Berman, Damini Dey, Piotr J. Slomka

npj Digit. Medicine, 2024

2023

Time and event-specific deep learning for personalized risk assessment after cardiac perfusion imaging.

Konrad Pieszko, Aakash D. Shanbhag, Ananya Singh, M. Timothy Hauser, Robert J. H. Miller, Joanna X. Liang, Manish Motwani, Jacek Kwiecinski, Tali Sharir, Andrew J. Einstein, Mathews Fish, Terrence D. Ruddy, Philipp A. Kaufmann, Albert J. Sinusas, Edward J. Miller, Timothy M. Bateman, Sharmila Dorbala, Marcelo Di Carli, Daniel S. Berman, Damini Dey, Piotr J. Slomka

npj Digit. Medicine, 2023

2022

Handling missing values in machine learning to predict patient-specific risk of adverse cardiac events: Insights from REFINE SPECT registry.

Richard Ríos, Robert J. H. Miller, Nipun Manral, Tali Sharir, Andrew J. Einstein, Mathews Fish, Terrence D. Ruddy, Philipp A. Kaufmann, Albert J. Sinusas, Edward J. Miller, Timothy M. Bateman, Sharmila Dorbala, Marcelo Di Carli, Serge D. Van Kriekinge, Paul Kavanagh, Tejas Parekh, Joanna X. Liang, Damini Dey, Daniel S. Berman, Piotr J. Slomka

Comput. Biol. Medicine, 2022