Ohcanbohtosat - Jayashree Kalpathy‐Cramer

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  1. 1
    Machine Learning Has Arrived!

    Machine Learning Has Arrived! Dahkki Aaron Lee, Paul Taylor, Jayashree Kalpathy‐Cramer, Adnan Tufail

    Almmustuhtton 2017
    Viečča ollesdeavstta Viečča ollesdeavstta
    Editorial
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  2. 2
    Accounting for data variability in multi-institutional distributed deep learning for medical imaging

    Accounting for data variability in multi-institutional distributed deep learning for medical imaging Dahkki Niranjan Balachandar, Ken Chang, Jayashree Kalpathy‐Cramer, Daniel L. Rubin

    Almmustuhtton 2020
    Viečča ollesdeavstta
    Artigo
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  3. 3
    Quantitative Imaging Network: Data Sharing and Competitive AlgorithmValidation Leveraging The Cancer Imaging Archive

    Quantitative Imaging Network: Data Sharing and Competitive AlgorithmValidation Leveraging The Cancer Imaging Archive Dahkki Jayashree Kalpathy‐Cramer, John Freymann, Justin Kirby, Paul E. Kinahan, Fred Prior

    Almmustuhtton 2014
    Viečča ollesdeavstta
    Artigo
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  4. 4
    Improving Automated Pediatric Bone Age Estimation Using Ensembles of Models from the 2017 RSNA Machine Learning Challenge

    Improving Automated Pediatric Bone Age Estimation Using Ensembles of Models from the 2017 RSNA Machine Learning Challenge Dahkki Ian Pan, Hans Henrik Thodberg, Safwan S. Halabi, Jayashree Kalpathy‐Cramer, David B. Larson

    Almmustuhtton 2019
    Viečča ollesdeavstta
    Artigo
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  5. 5
    A review of deep learning for brain tumor analysis in MRI

    A review of deep learning for brain tumor analysis in MRI Dahkki Felix J. Dorfner, Jay Patel, Jayashree Kalpathy-Cramer, Elizabeth R. Gerstner, Christopher P. Bridge

    Almmustuhtton 2025
    Viečča ollesdeavstta
    Revisão
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  6. 6
    Advanced Magnetic Resonance Imaging of the Physical Processes in Human Glioblastoma

    Advanced Magnetic Resonance Imaging of the Physical Processes in Human Glioblastoma Dahkki Jayashree Kalpathy‐Cramer, Elizabeth R. Gerstner, Kyrre E. Emblem, Ovidiu C. Andronesi, Bruce R. Rosen

    Almmustuhtton 2014
    Viečča ollesdeavstta
    Revisão
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  7. 7
    Personalized Radiotherapy Planning Based on a Computational Tumor Growth Model

    Personalized Radiotherapy Planning Based on a Computational Tumor Growth Model Dahkki Matthieu Lê, Hervé Delingette, Jayashree Kalpathy‐Cramer, Elizabeth R. Gerstner, Tracy Batchelor, Jan Unkelbach, Nicholas Ayache

    Almmustuhtton 2016
    Viečča ollesdeavstta
    Artigo
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  8. 8
    Implementation and Validation of a Three-dimensional Cardiac Motion Estimation Network

    Implementation and Validation of a Three-dimensional Cardiac Motion Estimation Network Dahkki Manuel A. Morales, David Izquierdo‐Garcia, Iman Aganj, Jayashree Kalpathy‐Cramer, Bruce R. Rosen, Ciprian Catana

    Almmustuhtton 2019
    Viečča ollesdeavstta
    Artigo
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  9. 9
    Artificial Intelligence in Retinopathy of Prematurity Diagnosis

    Artificial Intelligence in Retinopathy of Prematurity Diagnosis Dahkki Brittni A. Scruggs, R.V. Paul Chan, Jayashree Kalpathy‐Cramer, Michael F. Chiang, J. Peter Campbell

    Almmustuhtton 2020
    Viečča ollesdeavstta Viečča ollesdeavstta
    Revisão
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  10. 10
    Standard chemoradiation for glioblastoma results in progressive brain volume loss

    Standard chemoradiation for glioblastoma results in progressive brain volume loss Dahkki Morgan J. Prust, Kourosh Jafari‐Khouzani, Jayashree Kalpathy‐Cramer, Pavlina Polaskova, Tracy T. Batchelor, Elizabeth R. Gerstner, Jörg Dietrich

    Almmustuhtton 2015
    Viečča ollesdeavstta
    Artigo
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  11. 11
    High-resolution medical image synthesis using progressively grown generative adversarial networks

    High-resolution medical image synthesis using progressively grown generative adversarial networks Dahkki Andrew Beers, James M. Brown, Ken Chang, J. Peter Campbell, Susan Ostmo, Michael F. Chiang, Jayashree Kalpathy-Cramer

    Almmustuhtton 2018
    Viečča ollesdeavstta
    Pré-impressão
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  12. 12
    Transformer versus traditional natural language processing: how much data is enough for automated radiology report classification?

    Transformer versus traditional natural language processing: how much data is enough for automated radiology report classification? Dahkki Eric Yang, Matthew Li, Shruti Raghavan, Francis Deng, Min Lang, Marc D. Succi, Ambrose J. Huang, Jayashree Kalpathy-Cramer

    Almmustuhtton 2023
    Viečča ollesdeavstta Viečča ollesdeavstta
    Artigo
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  13. 13
    Dealing with inter-expert variability in retinopathy of prematurity: A machine learning approach

    Dealing with inter-expert variability in retinopathy of prematurity: A machine learning approach Dahkki Verónica Bolón‐Canedo, Esra Ataer-Cansızoğlu, Deniz Erdoğmuş, Jayashree Kalpathy‐Cramer, Óscar Fontenla-Romero, Amparo Alonso‐Betanzos, Michael F. Chiang

    Almmustuhtton 2015
    Viečča ollesdeavstta Viečča ollesdeavstta
    Artigo
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  14. 14
    Distributed deep learning networks among institutions for medical imaging

    Distributed deep learning networks among institutions for medical imaging Dahkki Ken Chang, Niranjan Balachandar, Carson Lam, Darvin Yi, James M. Brown, Andrew Beers, Bruce R. Rosen, Daniel L. Rubin, Jayashree Kalpathy‐Cramer

    Almmustuhtton 2018
    Viečča ollesdeavstta Viečča ollesdeavstta
    Artigo
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  15. 15
    Statistical issues in the comparison of quantitative imaging biomarker algorithms using pulmonary nodule volume as an example

    Statistical issues in the comparison of quantitative imaging biomarker algorithms using pulmonary nodule volume as an example Dahkki Nancy A. Obuchowski, Huiman X. Barnhart, Andrew J. Buckler, Gene Pennello, Xiaofeng Wang, Jayashree Kalpathy‐Cramer, Grace Hyun J. Kim, Anthony P. Reeves

    Almmustuhtton 2014
    Viečča ollesdeavstta
    Artigo
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  16. 16
    Nomogram for Predicting the Benefit of Adjuvant Chemoradiotherapy for Resected Gallbladder Cancer

    Nomogram for Predicting the Benefit of Adjuvant Chemoradiotherapy for Resected Gallbladder Cancer Dahkki Samuel J. Wang, Andrew Lemieux, Jayashree Kalpathy‐Cramer, Celine Bicquart Ord, Gary V. Walker, Clifton D. Fuller, Jong Sung Kim, Charles R. Thomas

    Almmustuhtton 2011
    Viečča ollesdeavstta Viečča ollesdeavstta
    Artigo
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  17. 17
    Repeatability of Standardized and Normalized Relative CBV in Patients with Newly Diagnosed Glioblastoma

    Repeatability of Standardized and Normalized Relative CBV in Patients with Newly Diagnosed Glioblastoma Dahkki Melissa Prah, Steven M. Stufflebeam, E.S. Paulson, Jayashree Kalpathy‐Cramer, Elizabeth R. Gerstner, Tracy T. Batchelor, Daniel P. Barboriak, Bruce R. Rosen, Kathleen M. Schmainda

    Almmustuhtton 2015
    Viečča ollesdeavstta Viečča ollesdeavstta
    Artigo
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  18. 18
    A Comparison of Lung Nodule Segmentation Algorithms: Methods and Results from a Multi-institutional Study

    A Comparison of Lung Nodule Segmentation Algorithms: Methods and Results from a Multi-institutional Study Dahkki Jayashree Kalpathy‐Cramer, Binsheng Zhao, Dmitry B. Goldgof, Irene Yu‐Hua Gu, Larry X. W. Wang, Hao Yang, Yongqiang Tan, Robert J. Gillies, Sandy Napel

    Almmustuhtton 2016
    Viečča ollesdeavstta
    Artigo
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  19. 19
    Improving the repeatability of deep learning models with Monte Carlo dropout

    Improving the repeatability of deep learning models with Monte Carlo dropout Dahkki Andréanne Lemay, Katharina Hoebel, Christopher P. Bridge, Brian Befano, Sílvia de Sanjosé, Didem Egemen, Ana Cecilia Rodríguez, Mark Schiffman, J. Peter Campbell, Jayashree Kalpathy‐Cramer

    Almmustuhtton 2022
    Viečča ollesdeavstta Viečča ollesdeavstta
    Artigo
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  20. 20
    Deepfakes in Ophthalmology

    Deepfakes in Ophthalmology Dahkki Jimmy Chen, Aaron S. Coyner, R.V. Paul Chan, M. Elizabeth Hartnett, Darius M. Moshfeghi, Leah A. Owen, Jayashree Kalpathy‐Cramer, Michael F. Chiang, J. Peter Campbell

    Almmustuhtton 2021
    Viečča ollesdeavstta Viečča ollesdeavstta
    Artigo
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