Gilmer Valdes
Gilmer Valdes
Geverifieerd e-mailadres voor ucsf.edu
Geciteerd door
Geciteerd door
Machine learning algorithms for outcome prediction in (chemo) radiotherapy: An empirical comparison of classifiers
TM Deist, FJWM Dankers, G Valdes, R Wijsman, IC Hsu, C Oberije, ...
Medical physics 45 (7), 3449-3459, 2018
Artificial intelligence and machine learning for medical imaging: A technology review
A Barragán-Montero, U Javaid, G Valdés, D Nguyen, P Desbordes, ...
Physica Medica 83, 242-256, 2021
Artificial intelligence in radiation oncology: a specialty-wide disruptive transformation?
RF Thompson, G Valdes, CD Fuller, CM Carpenter, O Morin, S Aneja, ...
Radiotherapy and Oncology 129 (3), 421-426, 2018
A mathematical framework for virtual IMRT QA using machine learning
G Valdes, R Scheuermann, CY Hung, A Olszanski, M Bellerive, ...
Medical physics 43 (7), 4323-4334, 2016
IMRT QA using machine learning: a multi‐institutional validation
G Valdes, MF Chan, SB Lim, R Scheuermann, JO Deasy, TD Solberg
Journal of applied clinical medical physics 18 (5), 279-284, 2017
MediBoost: a patient stratification tool for interpretable decision making in the era of precision medicine
G Valdes, JM Luna, E Eaton, CB Simone, LH Ungar, TD Solberg
Scientific reports 6 (1), 37854, 2016
Machine learning in radiation oncology: opportunities, requirements, and needs
M Feng, G Valdes, N Dixit, TD Solberg
Frontiers in oncology 8, 110, 2018
Expert-augmented machine learning
ED Gennatas, JH Friedman, LH Ungar, R Pirracchio, E Eaton, ...
Proceedings of the National Academy of Sciences 117 (9), 4571-4577, 2020
Deep nets vs expert designed features in medical physics: an IMRT QA case study
Y Interian, V Rideout, VP Kearney, E Gennatas, O Morin, J Cheung, ...
Medical physics 45 (6), 2672-2680, 2018
Clinical decision support of radiotherapy treatment planning: A data-driven machine learning strategy for patient-specific dosimetric decision making
G Valdes, CB Simone II, J Chen, A Lin, SS Yom, AJ Pattison, ...
Radiotherapy and Oncology 125 (3), 392-397, 2017
Integrated models incorporating radiologic and radiomic features predict meningioma grade, local failure, and overall survival
O Morin, WC Chen, F Nassiri, M Susko, ST Magill, HN Vasudevan, A Wu, ...
Neuro-Oncology Advances 1 (1), vdz011, 2019
A deep look into the future of quantitative imaging in oncology: a statement of working principles and proposal for change
O Morin, M Vallières, A Jochems, HC Woodruff, G Valdes, SE Braunstein, ...
International Journal of Radiation Oncology* Biology* Physics 102 (4), 1074-1082, 2018
Machine learning and modeling: Data, validation, communication challenges
I El Naqa, D Ruan, G Valdes, A Dekker, T McNutt, Y Ge, QJ Wu, JH Oh, ...
Medical physics 45 (10), e834-e840, 2018
Using machine learning to predict radiation pneumonitis in patients with stage I non-small cell lung cancer treated with stereotactic body radiation therapy
G Valdes, TD Solberg, M Heskel, L Ungar, CB Simone
Physics in Medicine & Biology 61 (16), 6105, 2016
Predicting radiation pneumonitis in locally advanced stage II–III non-small cell lung cancer using machine learning
JM Luna, HH Chao, ES Diffenderfer, G Valdes, C Chinniah, G Ma, ...
Radiotherapy and Oncology 133, 106-112, 2019
Integration of AI and machine learning in radiotherapy QA
MF Chan, A Witztum, G Valdes
Frontiers in artificial intelligence 3, 577620, 2020
Building more accurate decision trees with the additive tree
JM Luna, ED Gennatas, LH Ungar, E Eaton, ES Diffenderfer, ST Jensen, ...
Proceedings of the national academy of sciences 116 (40), 19887-19893, 2019
The application of artificial intelligence in the IMRT planning process for head and neck cancer
V Kearney, JW Chan, G Valdes, TD Solberg, SS Yom
Oral Oncology 87, 111-116, 2018
An unsupervised convolutional neural network-based algorithm for deformable image registration
V Kearney, S Haaf, A Sudhyadhom, G Valdes, TD Solberg
Physics in Medicine & Biology 63 (18), 185017, 2018
An artificial intelligence framework integrating longitudinal electronic health records with real-world data enables continuous pan-cancer prognostication
O Morin, M Vallières, S Braunstein, JB Ginart, T Upadhaya, HC Woodruff, ...
Nature Cancer 2 (7), 709-722, 2021
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