Hasil Pencarian - Collin M. Stultz

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  1. 1
    The effect of a DeltaK280 mutation on the unfolded state of a microtubule-binding repeat in Tau.

    The effect of a DeltaK280 mutation on the unfolded state of a microtubule-binding repeat in Tau. oleh Austin Huang, Collin M Stultz

    Diterbitkan 2008-01-01
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  2. 2
    Detecting QT prolongation from a single-lead ECG with deep learning.

    Detecting QT prolongation from a single-lead ECG with deep learning. oleh Ridwan Alam, Aaron Aguirre, Collin M Stultz

    Diterbitkan 2024-06-01
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  3. 3
    Detecting QT prolongation from a single-lead ECG with deep learning

    Detecting QT prolongation from a single-lead ECG with deep learning oleh Ridwan Alam, Aaron Aguirre, Collin M. Stultz

    Diterbitkan 2024-06-01
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  4. 4
    Intrinsically Disordered Proteins: Where Computation Meets Experiment

    Intrinsically Disordered Proteins: Where Computation Meets Experiment oleh Virginia M. Burger, Thomas Gurry, Collin M. Stultz

    Diterbitkan 2014-10-01
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  5. 5
    Fibronectin unfolding revisited: modeling cell traction-mediated unfolding of the tenth type-III repeat.

    Fibronectin unfolding revisited: modeling cell traction-mediated unfolding of the tenth type-III repeat. oleh Elaine P S Gee, Donald E Ingber, Collin M Stultz

    Diterbitkan 2008-01-01
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  6. 6
    DeepStrain: A Deep Learning Workflow for the Automated Characterization of Cardiac Mechanics

    DeepStrain: A Deep Learning Workflow for the Automated Characterization of Cardiac Mechanics oleh Manuel A. Morales, Manuel A. Morales, Maaike van den Boomen, Maaike van den Boomen, Maaike van den Boomen, Christopher Nguyen, Christopher Nguyen, Jayashree Kalpathy-Cramer, Bruce R. Rosen, Bruce R. Rosen, Collin M. Stultz, Collin M. Stultz, Collin M. Stultz, David Izquierdo-Garcia, David Izquierdo-Garcia, Ciprian Catana

    Diterbitkan 2021-09-01
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  7. 7
    Patient contrastive learning: A performant, expressive, and practical approach to electrocardiogram modeling.

    Patient contrastive learning: A performant, expressive, and practical approach to electrocardiogram modeling. oleh Nathaniel Diamant, Erik Reinertsen, Steven Song, Aaron D Aguirre, Collin M Stultz, Puneet Batra

    Diterbitkan 2022-02-01
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  8. 8
    ECG-guided non-invasive estimation of pulmonary congestion in patients with heart failure

    ECG-guided non-invasive estimation of pulmonary congestion in patients with heart failure oleh Aniruddh Raghu, Daphne Schlesinger, Eugene Pomerantsev, Srikanth Devireddy, Pinak Shah, Joseph Garasic, John Guttag, Collin M. Stultz

    Diterbitkan 2023-03-01
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  9. 9
    Identifying unreliable predictions in clinical risk models

    Identifying unreliable predictions in clinical risk models oleh Paul D. Myers, Kenney Ng, Kristen Severson, Uri Kartoun, Wangzhi Dai, Wei Huang, Frederick A. Anderson, Collin M. Stultz

    Diterbitkan 2020-01-01
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  10. 10
    Predicting outcomes in patients with aortic stenosis using machine learning: the Aortic Stenosis Risk (ASteRisk) score

    Predicting outcomes in patients with aortic stenosis using machine learning: the Aortic Stenosis Risk (ASteRisk) score oleh Philippe Pibarot, Romain Capoulade, Judy Hung, Michael H Picard, Mayooran Namasivayam, Paul D Myers, John V Guttag, Collin M Stultz

    Diterbitkan 2022-05-01
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