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Journal of Neurophysiology|February 11, 2011
Contributions of skin and muscle afferent input to movement sense in the human handPaul J Cordo, Jean-Louis Horn, Daniela Künster, et al.
Journal of Thoracic Imaging|March 14, 2023
Opportunistic Screening for Atrial Fibrillation on Routine Chest Computed TomographyWilliam A Parker, Davis M Vigneault, Issac Yang, et al.
Radiology. Cardiothoracic Imaging|March 29, 2021
Left Atrial Volume as a Biomarker of Atrial Fibrillation at Routine Chest CT: Deep Learning ApproachAlex Bratt, Zachary Guenther, Lewis D Hahn, et al.
Echocardiography (Mount Kisco, N.Y.)|May 13, 2020
Development of novel machine learning model for right ventricular quantification on echocardiography-A multimodality validation studyAshley N Beecy, Alex Bratt, Brian Yum, et al.
Proceedings of Spie--The International Society for Optical Engineering|May 25, 2026
Hallucination at low radiation dose: Evaluation of two deep-learning reconstruction methods in high-resolution chest CTZhongxing Zhou, Alex Bratt, Chi Wan Koo, et al.
European Radiology|June 9, 2022
Quantitative CT and machine learning classification of fibrotic interstitial lung diseasesChi Wan Koo, James M Williams, Grace Liu, et al.
Radiology|March 19, 2024
Photon-counting CT in Thoracic Imaging: Early Clinical Evidence and Incorporation Into Clinical PracticeJoel G Fletcher, Akitoshi Inoue, Alex Bratt, et al.
Frontiers in Cardiovascular Medicine|March 11, 2024
Predicting postoperative systolic dysfunction in mitral regurgitation: CT vs. echocardiographyPrajwal Reddy, Vidhu Anand, Prabhakar Rajiah, et al.
Journal of Digital Imaging|May 28, 2021
Deep Learning Improves the Temporal Reproducibility of Aortic MeasurementAlex Bratt, Daniel J Blezek, William J Ryan, et al.
Journal of Cardiovascular Magnetic Resonance : Official Journal of the Society for Cardiovascular Magnetic Resonance|January 8, 2019
Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantificationAlex Bratt, Jiwon Kim, Meridith Pollie, et al.
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