Search Results - Jethani, Neil

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  1. 1
    Abstract 17893: Deep Learning for the Prediction of Myocardial Scarring Through Electrocardiograms

    Abstract 17893: Deep Learning for the Prediction of Myocardial Scarring Through Electrocardiograms by Zhang, Jeff, Zhang, Hao, Jethani, Neil, CHINITZ, LARRY A, Aphinyanaphongs, Yindalon, Jankelson, Lior

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  2. 2
    Myocardial Injury in Adults Hospitalized With COVID-19

    Myocardial Injury in Adults Hospitalized With COVID-19 by Smilowitz, Nathaniel R., Jethani, Neil, Chen, Ji, Aphinyanaphongs, Yindalon, Zhang, Ruina, Dogra, Siddhant, Alviar, Carlos L., Keller, Norma, Razzouk, Louai, Quinones-Camacho, Adriana, Jung, Albert S., Fishman, Glenn I., Hochman, Judith S., Berger, Jeffrey S.

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  3. 3
    Estimating real-world performance of a predictive model: a case-study in predicting mortality

    Estimating real-world performance of a predictive model: a case-study in predicting mortality by Major, Vincent J, Jethani, Neil, Aphinyanaphongs, Yindalon

    Published in JAMIA open
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  4. 4
    Abstract 13299: Myocardial Injury in Adults Hospitalized With Covid-19

    Abstract 13299: Myocardial Injury in Adults Hospitalized With Covid-19 by Smilowitz, Nathaniel R, Jethani, Neil, Chen, Ji, Aphinyanaphongs, Yindalon, Zhang, Ruina, Dogra, Siddhant, Alviar, Carlos, Keller, Norma M, Razzouk, Louai, Quinones-Camacho, Adriana, Jung, Albert S, Fishman, Glenn I, Hochman, Judith S, Berger, Jeffrey S

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  5. 5
    Development and external validation of a dynamic risk score for early prediction of cardiogenic shock in cardiac intensive care units using machine learning

    Development and external validation of a dynamic risk score for early prediction of cardiogenic shock in cardiac intensive care units using machine learning by Hu, Yuxuan, Lui, Albert, Goldstein, Mark, Sudarshan, Mukund, Tinsay, Andrea, Tsui, Cindy, Maidman, Samuel D, Medamana, John, Jethani, Neil, Puli, Aahlad, Nguy, Vuthy, Aphinyanaphongs, Yindalon, Kiefer, Nicholas, Smilowitz, Nathaniel R, Horowitz, James, Ahuja, Tania, Fishman, Glenn I, Hochman, Judith, Katz, Stuart, Bernard, Samuel, Ranganath, Rajesh

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  6. 6
    Evaluating Large Language Models in extracting cognitive exam dates and scores

    Evaluating Large Language Models in extracting cognitive exam dates and scores by Zhang, Hao, Jethani, Neil, Jones, Simon, Genes, Nicholas, Major, Vincent J, Jaffe, Ian S, Cardillo, Anthony B, Heilenbach, Noah, Ali, Nadia Fazal, Bonanni, Luke J, Clayburn, Andrew J, Khera, Zain, Sadler, Erica C, Prasad, Jaideep, Schlacter, Jamie, Liu, Kevin, Silva, Benjamin, Montgomery, Sophie, Kim, Eric J, Lester, Jacob, Hill, Theodore M, Avoricani, Alba, Chervonski, Ethan, Davydov, James, Small, William, Chakravartty, Eesha, Grover, Himanshu, Dodson, John A, Brody, Abraham A, Aphinyanaphongs, Yindalon, Masurkar, Arjun, Razavian, Narges

    Published in PLOS digital health
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  7. 7
    Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation

    Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation by Jethani, Neil, Saporta, Adriel, Ranganath, Rajesh

    Published in arXiv.org
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  8. 8
    New-Onset Diabetes Assessment Using Artificial Intelligence-Enhanced Electrocardiography

    New-Onset Diabetes Assessment Using Artificial Intelligence-Enhanced Electrocardiography by Jethani, Neil, Puli, Aahlad, Zhang, Hao, Garber, Leonid, Jankelson, Lior, Aphinyanaphongs, Yindalon, Ranganath, Rajesh

    Published in arXiv.org
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  9. 9
    Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations

    Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations by Jethani, Neil, Sudarshan, Mukund, Aphinyanaphongs, Yindalon, Ranganath, Rajesh

    Published in arXiv.org
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  10. 10
    FastSHAP: Real-Time Shapley Value Estimation

    FastSHAP: Real-Time Shapley Value Estimation by Jethani, Neil, Sudarshan, Mukund, Covert, Ian, Lee, Su-In, Ranganath, Rajesh

    Published in arXiv.org
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  11. 11
    A dynamic risk score for early prediction of cardiogenic shock using machine learning

    A dynamic risk score for early prediction of cardiogenic shock using machine learning by Hu, Yuxuan, Lui, Albert, Goldstein, Mark, Sudarshan, Mukund, Tinsay, Andrea, Tsui, Cindy, Maidman, Samuel, Medamana, John, Jethani, Neil, Puli, Aahlad, Nguy, Vuthy, Aphinyanaphongs, Yindalon, Kiefer, Nicholas, Smilowitz, Nathaniel, Horowitz, James, Ahuja, Tania, Fishman, Glenn I, Hochman, Judith, Katz, Stuart, Bernard, Samuel, Ranganath, Rajesh

    Published in arXiv.org
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