检索结果 - Valdes, Gilmer

Integration of AI and Machine Learning in Radiotherapy QA 由 Chan, Maria F., Witztum, Alon, Valdes, Gilmer

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Machine Learning in Radiation Oncology: Opportunities, Requirements, and Needs 由 Feng, Mary, Valdes, Gilmer, Dixit, Nayha, Solberg, Timothy D.

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Risks and Opportunities to Ensure Equity in the Application of Big Data Research in Public Health 由 Wesson, Paul, Hswen, Yulin, Valdes, Gilmer, Stojonowski, Kristefer, Handley, Margaret A

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Using Machine Learning to Predict Radiation Pneumonitis in Patients with Stage I Non-Small Cell Lung Cancer Treated with Stereotactic Body Radiation Therapy 由 Valdes, Gilmer, Solberg, Timothy D., Heskel, Marina, Ungar, Lyle, Simone, Charles B.

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Use of TrueBeam developer mode for imaging QA 由 Valdes, Gilmer, Morin, Olivier, Valenciaga, Yanisley, Kirby, Niel, Pouliot, Jean, Chuang, Cynthia

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MediBoost: a Patient Stratification Tool for Interpretable Decision Making in the Era of Precision Medicine 由 Valdes, Gilmer, Luna, José Marcio, Eaton, Eric, Simone, Charles B., Ungar, Lyle H., Solberg, Timothy D.

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IMRT QA using machine learning: A multi‐institutional validation 由 Valdes, Gilmer, Chan, Maria F., Lim, Seng Boh, Scheuermann, Ryan, Deasy, Joseph O., Solberg, Timothy D.

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Exploratory analysis using machine learning to predict for chest wall pain in patients with stage I non‐small‐cell lung cancer treated with stereotactic body radiation therapy 由 Chao, Hann‐Hsiang, Valdes, Gilmer, Luna, Jose M., Heskel, Marina, Berman, Abigail T., Solberg, Timothy D., Simone, Charles B.

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NIMG-67. CLINICAL APPLICATIONS OF QUANTITATIVE THREE-DIMENSIONAL MRI ANALYSIS FOR PEDIATRIC EMBRYONAL BRAIN TUMORS 由 Hara, Jared, Wu, Ashley, Villanueva-Meyer, Javier, Valdes, Gilmer, Daggubati, Vikas, Mueller, Sabine, Solberg, Timothy, Braunstein, Steve, Morin, Olivier, Raleigh, David

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A Situational Awareness Bayesian Network Approach for Accurate and Credible Personalized Adaptive Radiotherapy Outcomes Prediction in Lung Cancer Patients 由 Luo, Yi, Jolly, Shruti, Palma, David, Lawrence, Theodore S., Tseng, Huan-Hsin, Valdes, Gilmer, McShan, Daniel, Ten Haken, Randall K., Naqa, Issam EI

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Artificial Intelligence-Guided Prediction of Dental Doses Before Planning of Radiation Therapy for Oropharyngeal Cancer: Technical Development and Initial Feasibility of Implementa... 由 Chan, Jason W., Hohenstein, Nicole, Carpenter, Colin, Pattison, Adam J., Morin, Olivier, Valdes, Gilmer, Sanchez, Cristina Tolentino, Perkins, Jennifer, Solberg, Timothy D., Yom, Sue S.

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Building more accurate decision trees with the additive tree 由 Luna, José Marcio, Gennatas, Efstathios D., Ungar, Lyle H., Eaton, Eric, Diffenderfer, Eric S., Jensen, Shane T., Simone, Charles B., Friedman, Jerome H., Solberg, Timothy D., Valdes, Gilmer

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Reply to Nock and Nielsen: On the work of Nock and Nielsen and its relationship to the additive tree 由 Valdes, Gilmer, Luna, José Marcio, Gennatas, Efstathios D., Ungar, Lyle H., Eaton, Eric, Diffenderfer, Eric S., Jensen, Shane T., Simone, Charles B., Friedman, Jerome H., Solberg, Timothy D.

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Radio-sensitization of gliomas by intracellular generation of 5-fluorouracil potentiates prodrug activator gene therapy with a retroviral replicating vector 由 Takahashi, Masamichi, Valdes, Gilmer, Hiraoka, Kei, Inagaki, Akihito, Kamijima, Shuichi, Micewicz, Ewa, Gruber, Harry E., Robbins, Joan M., Jolly, Douglas J., McBride, William H., Iwamoto, Keisuke S., Kasahara, Noriyuki

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Artificial intelligence and machine learning for medical imaging: a technology review 由 Barragán-Montero, Ana, Javaid, Umair, Valdés, Gilmer, Nguyen, Dan, Desbordes, Paul, Macq, Benoit, Willems, Siri, Vandewinckele, Liesbeth, Holmström, Mats, Löfman, Fredrik, Michiels, Steven, Souris, Kevin, Sterpin, Edmond, Lee, John A.

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MNGI-23. PREOPERATIVE QUANTITATIVE IMAGING FEATURES ARE PROGNOSTIC FOR MENINGIOMA OUTCOMES 由 Morin, Oliver, Chen, William, Gennatas, Efstathios, Magill, Stephen, Wu, Ashley, Valdes, Gilmer, Perry, Arie, Sneed, Penny, McDermott, Michael, Solberg, Timothy, Bush, Nancy Ann Oberheim, Braunstein, Steve, Villanueva-Meyer, Javier, Raleigh, David

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ET-60 ENHANCED THERAPEUTIC EFFICACY OF PRODRUG ACTIVATOR GENE THERAPY WITH A NON-LYTIC RETROVIRAL REPLICATING VECTOR (TOCA 511) COMBINED WITH RADIATION THERAPY IN EXPERIMENTAL GLIO... 由 Takahashi, Masamichi, Valdes, Gilmer, Inagaki, Akihito, Kamijima, Shuichi, Hiraoka, Kei, Micewicz, Ewa, McBride, William H., Iwamoto, Keisuke S., Hermann, Kip, Collins, Sara, Tam, Quincy, Gruber, Harry E., Robbins, Joan M., Jolly, Douglas J., Kasahara, Noriyuki

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Preoperative and postoperative prediction of long-term meningioma outcomes 由 Gennatas, Efstathios D., Wu, Ashley, Braunstein, Steve E., Morin, Olivier, Chen, William C., Magill, Stephen T., Gopinath, Chetna, Villaneueva-Meyer, Javier E., Perry, Arie, McDermott, Michael W., Solberg, Timothy D., Valdes, Gilmer, Raleigh, David R.

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Expert-augmented machine learning 由 Gennatas, Efstathios D., Friedman, Jerome H., Ungar, Lyle H., Pirracchio, Romain, Eaton, Eric, Reichmann, Lara G., Interian, Yannet, Luna, José Marcio, Simone, Charles B., Auerbach, Andrew, Delgado, Elier, van der Laan, Mark J., Solberg, Timothy D., Valdes, Gilmer

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Machine learning and modeling: Data, validation, communication challenges 由 El Naqa, Issam, Ruan, Dan, Valdes, Gilmer, Dekker, Andre, McNutt, Todd, Ge, Yaorong, Wu, Q. Jackie, Oh, Jung Hun, Thor, Maria, Smith, Wade, Rao, Arvind, Fuller, Clifton, Xiao, Ying, Manion, Frank, Schipper, Matthew, Mayo, Charles, Moran, Jean M., Ten Haken, Randall

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