Suchergebnisse - Ha, Richard

Understanding artificial intelligence based radiology studies: What is overfitting? von Mutasa, Simukayi, Sun, Shawn, Ha, Richard

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Commentary: Superior vena cava syndrome should not hinder use of a percutaneous right ventricular assist device von Ha, Richard V., Nguyen, Tom C.

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Optimal timing of same-admission orthotopic heart transplantation after left ventricular assist device implantation von Gulati, Gunsagar, Ouyang, David, Ha, Richard, Banerjee, Dipanjan

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Should We Ignore, Follow, or Biopsy? Impact of Artificial Intelligence Decision Support on Breast Ultrasound Lesion Assessment von Mango, Victoria L., Sun, Mary, Wynn, Ralph T., Ha, Richard

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Ultrasonographic features and clinical implications of benign palpable breast lesions in young women von Ha, Richard, Kim, Hyonah, Mango, Victoria, Wynn, Ralph, Comstock, Christopher

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Innovations in image-guided preoperative breast lesion localization von Cheang, Ellen, Ha, Richard, Thornton, Cynthia M, Mango, Victoria L

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Biventricular VAD versus LVAD for right heart failure von Boulate, David, Marques, Michael A., Ha, Richard, Banerjee, Dipanjan, Haddad, Francois

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Breast MRI Screening for Average-Risk Women: A Monte Carlo Simulation Cost–Benefit Analysis von Mango, Victoria L., Goel, Akshay, Mema, Eralda, Kwak, Ellie, Ha, Richard

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Simultaneous ramp right heart catheterization and echocardiography in a ReliantHeart left ventricular assist device von Banerjee, Dipanjan, Dutt, Debleena, Duclos, Sebastien, Sallam, Karim, Wheeler, Matthew, Ha, Richard

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Dynamic Changes of Convolutional Neural Network-based Mammographic Breast Cancer Risk Score Among Women Undergoing Chemoprevention Treatment von Manley, Haley, Mutasa, Simukayi, Chang, Peter, Desperito, Elise, Crew, Katherine, Ha, Richard

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A novel CNN algorithm for pathological complete response prediction using an I-SPY TRIAL breast MRI database von Liu, Michael Z., Mutasa, Simukayi, Chang, Peter, Siddique, Maham, Jambawalikar, Sachin, Ha, Richard

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Quantitative 3D breast magnetic resonance imaging fibroglandular tissue analysis and correlation with qualitative assessments: a feasibility study von Ha, Richard, Mema, Eralda, Guo, Xiaotao, Mango, Victoria, Desperito, Elise, Ha, Jason, Wynn, Ralph, Zhao, Binsheng

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A Single-Institution Experience in the Preoperative Selection of DCIS Patients for IORT using the ASTRO Consensus Guidelines von Chin, Christine, Hirji, Sitara, Onishi, Maika, Ha, Richard, Taback, Bret, Horowitz, David P., Connolly, Eileen P.

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Stereotactic breast biopsy efficiency: Does a pre-biopsy grid image help? von Mango, Victoria L., D’Alessio, Donna, Morris, Elizabeth A., Ha, Richard, Bernard-Davila, Blanca, Jochelson, Maxine S.

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Influence of Durable Mechanical Circulatory Support and Allosensitization on Mortality After Heart Transplantation von Chiu, Peter, Schaffer, Justin M., Oyer, Philip E., Pham, Michael, Banerjee, Dipanjan, Woo, Y. Joseph, Ha, Richard

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Evaluation of Partial Breast Reirradiation with Intraoperative Radiotherapy after Prior Thoracic Radiation: A Single-Institution Report of Outcomes and Toxicity von Chin, Christine, Jadeja, Priya, Taback, Bret, Horowitz, David P., Feldman, Sheldon M., Ha, Richard, Connolly, Eileen P.

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Axillary Lymph Node Evaluation Utilizing Convolutional Neural Networks Using MRI Dataset von Ha, Richard, Chang, Peter, Karcich, Jenika, Mutasa, Simukayi, Fardanesh, Reza, Wynn, Ralph T., Liu, Michael Z., Jambawalikar, Sachin

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Fully Automated Convolutional Neural Network Method for Quantification of Breast MRI Fibroglandular Tissue and Background Parenchymal Enhancement von Ha, Richard, Chang, Peter, Mema, Eralda, Mutasa, Simukayi, Karcich, Jenika, Wynn, Ralph T., Liu, Michael Z., Jambawalikar, Sachin

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Accuracy of Distinguishing Atypical Ductal Hyperplasia From Ductal Carcinoma In Situ With Convolutional Neural Network–Based Machine Learning Approach Using Mammographic Image Data... von Ha, Richard, Mutasa, Simukayi, Sant, Eduardo Pascual Van, Karcich, Jenika, Chin, Christine, Liu, Michael Z., Jambawalikar, Sachin

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Convolutional Neural Network Based Breast Cancer Risk Stratification Using a Mammographic Dataset von Ha, Richard, Chang, Peter, Karcich, Jenika, Mutasa, Simukayi, Pascual Van Sant, Eduardo, Liu, Michael Z., Jambawalikar, Sachin

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