A mathematical modelling tool for predicting survival of individual patients following resection of glioblastoma: a proof of principle von Swanson, K R, Rostomily, R C, Alvord, E C

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Predicting the efficacy of radiotherapy in individual glioblastoma patients in vivo: a mathematical modeling approach von Rockne, R, Rockhill, J K, Mrugala, M, Spence, A M, Kalet, I, Hendrickson, K, Lai, A, Cloughesy, T, Alvord, E C, Swanson, K R

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Analysis of glioblastoma tumor coverage by oncolytic virus-loaded neural stem cells using MRI-based tracking and histological reconstruction von Morshed, R A, Gutova, M, Juliano, J, Barish, M E, Hawkins-Daarud, A, Oganesyan, D, Vazgen, K, Yang, T, Annala, A, Ahmed, A U, Aboody, K S, Swanson, K R, Moats, R A, Lesniak, M S

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Virtual brain tumours (gliomas) enhance the reality of medical imaging and highlight inadequacies of current therapy von Swanson, K R, Alvord, E C, Murray, J D

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From patient-specific mathematical neuro-oncology to precision medicine von Baldock, A L, Rockne, R C, Boone, A D, Neal, M L, Hawkins-Daarud, A, Corwin, D M, Bridge, C A, Guyman, L A, Trister, A D, Mrugala, M M, Rockhill, J K, Swanson, K R

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The biology and mathematical modelling of glioma invasion: a review von Alfonso, J. C. L., Talkenberger, K., Seifert, M., Klink, B., Hawkins-Daarud, A., Swanson, K. R., Hatzikirou, H., Deutsch, A.

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A quantitative model for differential motility of gliomas in grey and white matter von Swanson, K. R., Alvord, E. C., Murray, J. D.

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Performance of Standardized Relative CBV for Quantifying Regional Histologic Tumor Burden in Recurrent High-Grade Glioma: Comparison against Normalized Relative CBV Using Image-Loc... von Hoxworth, J M, Eschbacher, J M, Gonzales, A C, Singleton, K W, Leon, G D, Smith, K A, Stokes, A M, Zhou, Y, Mazza, G L, Porter, A B, Mrugala, M M, Zimmerman, R S, Bendok, B R, Patra, D P, Krishna, C, Boxerman, J L, Baxter, L C, Swanson, K R, Quarles, C C, Schmainda, K M, Hu, L S

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A mathematical model for brain tumor response to radiation therapy von Rockne, R., Alvord, E. C., Rockhill, J. K., Swanson, K. R.

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Accurate Patient-Specific Machine Learning Models of Glioblastoma Invasion Using Transfer Learning von Hu, L S, Yoon, H, Eschbacher, J M, Baxter, L C, Dueck, A C, Nespodzany, A, Smith, K A, Nakaji, P, Xu, Y, Wang, L, Karis, J P, Hawkins-Daarud, A J, Singleton, K W, Jackson, P R, Anderies, B J, Bendok, B R, Zimmerman, R S, Quarles, C, Porter-Umphrey, A B, Mrugala, M M, Sharma, A, Hoxworth, J M, Sattur, M G, Sanai, N, Koulemberis, P E, Krishna, C, Mitchell, J R, Wu, T, Tran, N L, Swanson, K R, Li, J

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Correlation of in vitro infiltration with glioma histological type in organotypic brain slices von Palfi, S, Swanson, K R, de Boüard, S, Chrétien, F, Oliveira, R, Gherardi, R K, Kros, J M, Peschanski, M, Christov, C

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Adaptive IMRT using a multiobjective evolutionary algorithm integrated with a diffusion-invasion model of glioblastoma von Holdsworth, C H, Corwin, D, Stewart, R D, Rockne, R, Trister, A D, Swanson, K R, Phillips, M

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Reply to comment on: 'Predicting the efficacy of radiotherapy in individual glioblastoma patients in vivo: a mathematical modeling approach' von Rockne, R, Rockhill, J K, Mrugala, M, Spence, A M, Kalet, I, Hendrickson, K, Lai, A, Cloughesy, T, Alvord, E C, Swanson, K R

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Velocity of Radial Expansion of Contrast-enhancing Gliomas and the Effectiveness of Radiotherapy in Individual Patients: a Proof of Principle von Swanson, K.R, Harpold, H.L.P, Peacock, D.L, Rockne, R, Pennington, C, Kilbride, L, Grant, R, Wardlaw, J.M, Alvord, E.C

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Structure and fragility of normal and invert lanthanum borate glasses: Results from 11B and 17O NMR spectroscopy and calorimetry von Swanson, R.K., Stebbins, J.F., Yeo, T.M., Xu, Y., Hung, I., Gan, Z., McCormack, S.J., Sen, S.

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An application for near-real-time analysis of XPS data von Lea, A. S., Swanson, K. R., Haack, J. N., Castle, J. E., Tougaard, S., Baer, D. R.

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The Evolution of Mathematical Modeling of Glioma Proliferation and Invasion von Harpold, Hana L.P, Alvord, Ellsworth C, Swanson, Kristin R

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Deep neural network to locate and segment brain tumors outperformed the expert technicians who created the training data von Mitchell, JR, Kamnitsas, K, Singleton, KW, Whitmire, SA, Clark-Swanson, KR, Ranjbar, S, Rickertsen, CR, Johnston, SK, Egan, KM, Rollison, DE, Arrington, J, Krecke, KN, Passe, TJ, Verdoorn, JT, Nagelschneider, AA, Carr, CM, Port, JD, Patton, A, Campeau, NG, Liebo, GB, Eckel, LJ, Wood, CP, Hunt, CH, Vibhute, P, Nelson, KD, Hoxworth, JM, Patel, AC, Chong, BW, Ross, JS, Boxerman, JL, Vogelbaum, MA, Hu, LS, Glocker, B, Swanson, KR

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Virtual resection of gliomas: Effect of extent of resection on recurrence von Swanson, K.R, Alvord, E.C, Murray, J.D

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A Quantitative Model for the Dynamics of Serum Prostate-Specific Antigen as a Marker for Cancerous Growth : An Explanation for a Medical Anomaly von Swanson, Kristin R, True, Lawrence D, Lin, Daniel W, Buhler, Kent R, Vessella, Robert, Murray, James D

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