Right Ventricular Strain, Torsion, and Dyssynchrony in Healthy Subjects Using 3D Spiral Cine DENSE Magnetic Resonance Imaging. - Jonathan D. Suever; Gregory J. Wehner; Linyuan Jing; David K. Powell; Sean M. Hamlet; Jonathan D. Grabau; Dimitri Mojsejenko; Kristin N. Andres; Christopher M. Haggerty; Brandon K. Fornwalt (IEEE Trans. Medical Imaging, 2017)

Ventricular segmentation and quantitative assessment in cardiac MR using convolutional neural networks. - Joshua V. Stough; Joseph DiPalma; Zilin Ma; Brandon K. Fornwalt; Christopher M. Haggerty (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2018)

A deep neural network predicts survival after heart imaging better than cardiologists. - Alvaro Ulloa; Linyuan Jing; Christopher W. Good; David P. vanMaanen; Sushravya Raghunath; Jonathan D. Suever; Christopher D. Nevius; Gregory J. Wehner; Dustin N. Hartzel; Joseph B. Leader; Amro Alsaid; Aalpen A. Patel; et al. (CoRR, 2018)

Advanced machine learning in action: identification of intracranial hemorrhage on computed tomography scans of the head with clinical workflow integration. - Mohammad R. Arbabshirani; Brandon K. Fornwalt; Gino J. Mongelluzzo; Jonathan D. Suever; Brandon D. Geise; Aalpen A. Patel; Gregory J. Moore (npj Digit. Medicine, 2018)

Interpretable Neural Networks for Predicting Mortality Risk using Multi-modal Electronic Health Records. - Alvaro E. Ulloa Cerna; Marios Pattichis; David P. vanMaanen; Linyuan Jing; Aalpen A. Patel; Joshua V. Stough; Christopher M. Haggerty; Brandon K. Fornwalt (CoRR, 2019)

Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data. - Sushravya Raghunath; Alvaro E. Ulloa Cerna; Linyuan Jing; David P. vanMaanen; Joshua Stough; Dustin N. Hartzel; Joseph B. Leader; H. Lester Kirchner; Christopher W. Good; Aalpen A. Patel; Brian P. Delisle; Amro Alsaid; et al. (CoRR, 2019)

Left ventricular and atrial segmentation of 2D echocardiography with convolutional neural networks. - Joshua V. Stough; Sushravya Raghunath; Xiaoyan Zhang; John M. Pfeifer; Brandon K. Fornwalt; Christopher M. Haggerty (Image Processing, 2020)

OASIS +: leveraging machine learning to improve the prognostic accuracy of OASIS severity score for predicting in-hospital mortality. - Yasser El-Manzalawy; Mostafa M. Abbas; Ian Hoaglund; Alvaro Ulloa Cerna; Thomas B. Morland; Christopher M. Haggerty; Eric S. Hall; Brandon K. Fornwalt (BMC Medical Informatics Decis. Mak., 2021)

A Comparative Analysis of Data-Driven Modelling Techniques for 30-Day Heart Failure Readmission Prediction. - Ryan Missel; Jesdin Raphael; Christopher M. Haggerty; Dustin N. Hartzel; Jeffery Ruhl; Brandon K. Fornwalt; Linwei Wang (CinC, 2023)

Large Language Models with Retrieval-Augmented Generation for Zero-Shot Disease Phenotyping. - Will E. Thompson; David M. Vidmar; Jessica K. De Freitas; John M. Pfeifer; Brandon K. Fornwalt; Ruijun Chen; Gabriel Altay; Kabir Manghnani; Andrew C. Nelsen; Kellie Morland; Martin C. Stumpe; Riccardo Miotto (CoRR, 2023)

A probabilistic approach for building disease phenotypes across electronic health records. - David M. Vidmar; Jessica K. De Freitas; Will E. Thompson; John M. Pfeifer; Brandon K. Fornwalt; Noah Zimmerman; Riccardo Miotto; Ruijun Chen (BioData Min., 2025)

A Large-scale Multimodal Study for Predicting Mortality Risk Using Minimal and Low Parameter Models and Separable Risk Assessment. - Alvaro E. Ulloa Cerna; David P. vanMaanen; Linyuan Jing; Joshua V. Stough; Aalpen A. Patel; Christopher M. Haggerty; Brandon K. Fornwalt; Marios S. Pattichis (IEEE J. Biomed. Health Informatics, 2025)