Robert J. H. Miller

According to our database, Robert J. H. Miller authored at least 9 papers between 2022 and 2026.

Collaborative distances:

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

2026

Multicenter evaluation of interpretable AI for coronary artery disease diagnosis from PET biomarkers.

Wenhao Zhang, Jacek Kwiecinski, Aakash D. Shanbhag, Robert J. H. Miller, Shiva Mostafavi, Giselle Ramirez, Jirong Yi, Donghee Han, Damini Dey, Dominika Grodecka, Kajetan Grodecki, Mark Lemley, Paul Kavanagh, Joanna X. Liang, Jianhang Zhou, Valerie Builoff, Jon Hainer, Sylvain Carre, Leanne Barrett, Andrew J. Einstein, Stacey Knight, Steve Mason, Viet T. Le, Wanda Acampa, Samuel Wopperer, Panithaya Chareonthaitawee, Daniel S. Berman, Marcelo Di Carli, Piotr J. Slomka

npj Digit. Medicine, 2026

2025

Holistic AI analysis of hybrid cardiac perfusion images for mortality prediction.

Anna M. Marcinkiewicz, Wenhao Zhang, Aakash D. Shanbhag, Robert J. H. Miller, Mark Lemley, Giselle Ramirez, Mikolaj Buchwald, Aditya Killekar, Paul Kavanagh, Attila Feher, Edward J. Miller, Andrew J. Einstein, Terrence D. Ruddy, Joanna X. Liang, Valerie Builoff, David Ouyang, Daniel S. Berman, Damini Dey, Piotr J. Slomka

npj Digit. Medicine, 2025

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

Improving 1-Year Mortality Prediction After Pediatric Heart Transplantation Using Hypothetical Donor-Recipient Matches.

Michela Venturini, Fateme Nateghi Haredasht, Frantisek Sabovcik, Robert J. H. Miller, Tatiana Kuznetsova, Celine Vens

IEEE Access, 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

Comparative analysis between convolutional long short-term memory networks and vision transformers for coronary calcium scoring in non-contrast CT.

Aakash D. Shanbhag, Konrad Pieszko, Robert J. H. Miller, Aditya Killekar, Waechter Parker, Heidi Gransar, Michelle Williams, Daniel S. Berman, Damini Dey, Piotr J. Slomka

Proceedings of the Medical Imaging 2023: Image Processing, 2023

Transferring deep convolutional network representations from SPECT to improve PET cardiac outcome prediction.

Bryan P. Bednarski, Aakash D. Shanbhag, Ananya Singh, Robert J. H. Miller, Heidi Gransar, Keiichiro Kuronuma, Tali Sharir, Sharmila Dorbala, Marcelo Di Carli, Matthews B. Fish, Terrence D. Ruddy, Daniel S. Berman, Damini Dey, Piotr J. Slomka

Proceedings of the Medical Imaging 2023: Image Processing, 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

Calcium scoring in low-dose ungated chest CT scans using convolutional long-short term memory networks.

Konrad Pieszko, Aakash D. Shanbhag, Aditya Killekar, Mark Lemley, Yuka Otaki, Serge D. Van Kriekinge, Paul Kavanagh, Robert J. H. Miller, Edward J. Miller, Timothy M. Bateman, Damini Dey, Daniel S. Berman, Piotr J. Slomka

Proceedings of the Medical Imaging 2022: Image Processing, 2022