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Graduate in Mathematics (2010) and Computer Science (2010) at Universidad Autónoma de Madrid. MsC on Mathematics and applications at Universidad Autónoma de Madrid (2011). PhD in Mathematics (2015) at Universidad de Castilla-La Mancha. His research interests are discrete mathematics, machine learning, image processing and their applications to Mathematical Biology. |
Publications
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Intratumoral heterogeneity in 18F-FDG PET/CT by textural analysis in breast cancer as predictive and prognostic subrogate.
Annals of Nuclear Medicine 32(6), 379-388 (2018).
D. Molina A.M. García Vicente, J. Pérez-Beteta, M. Amo-Salas, A. Martínez-González, M.J. Tello Galán, A. Soriano, V.M. Pérez-García -
Towards Uncertainty-Assisted Brain Tumor Segmentation and Survival Prediction
In: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2017. Lecture Notes in Computer Science, vol 10670. Springer
A. Jungo, R. McKinley, R. Meier, U. Knecht, L. Vera, J. Pérez-Beteta, D. Molina, V.M. Pérez-García, R. Wiest, M. Reyes -
Tumor Surface Regularity at MR Imaging Predicts Survival and Response to Surgery in Patients with Glioblastoma
Radiology 288(1), 218-225 (2018)
J. Pérez-Beteta, D. Molina, A. Fernández, B. Luque, E. Arregui, M. Calvo, J. M. Borrás, A. Fernández-Romero, B. Luque, B. Meléndez, A.R. de Lope, R. Moreno, L. Iglesias, J.A. Barcia, J. Martino, C. Velasquez, B. Asenjo, M. Benavides, I. Herruzo, A. Revert, E. Arana, V. M. Pérez-García
Projects
- Establishing a non-invasive approach to accurately diagnose and assess brain tumors
Canadian Cancer Society (2024 - 2027) - Improving New Therapies in Oncology and Related Fields using mathematical models and biomedical data
Ministry of Science and Innovation (National Research Plan) (2023 - 2026) - Mathematical models for the digital transition in neuro-oncology: In-silico design of a clinical trial for glioblastoma.
Ministerio de Ciencia e Innovación (NextGenerationEU) (2023 - 2024) - Validation and transfer of oncological data and biomarkers based on mathematical models (AFTERbioMATH)
Ministry of Science and Innovation (Spain), Proof of Concept Program (2023 - 2024) - Mathematical models in Oncology
Ministerio de Ciencia e Innovación (Spain) (2020 - 2023)
Molina García, David
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Graduate in Mathematics (2010) and Computer Science (2010) at Universidad Autónoma de Madrid. MsC on Mathematics and applications at Universidad Autónoma de Madrid (2011). PhD in Mathematics (2015) at Universidad de Castilla-La Mancha. His research interests are discrete mathematics, machine learning, image processing and their applications to Mathematical Biology. |
Publications
- Intratumoral heterogeneity in 18F-FDG PET/CT by textural analysis in breast cancer as predictive and prognostic subrogate.
Annals of Nuclear Medicine 32(6), 379-388 (2018).
D. Molina A.M. García Vicente, J. Pérez-Beteta, M. Amo-Salas, A. Martínez-González, M.J. Tello Galán, A. Soriano, V.M. Pérez-García - Towards Uncertainty-Assisted Brain Tumor Segmentation and Survival Prediction
In: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2017. Lecture Notes in Computer Science, vol 10670. Springer
A. Jungo, R. McKinley, R. Meier, U. Knecht, L. Vera, J. Pérez-Beteta, D. Molina, V.M. Pérez-García, R. Wiest, M. Reyes - Tumor Surface Regularity at MR Imaging Predicts Survival and Response to Surgery in Patients with Glioblastoma
Radiology 288(1), 218-225 (2018)
J. Pérez-Beteta, D. Molina, A. Fernández, B. Luque, E. Arregui, M. Calvo, J. M. Borrás, A. Fernández-Romero, B. Luque, B. Meléndez, A.R. de Lope, R. Moreno, L. Iglesias, J.A. Barcia, J. Martino, C. Velasquez, B. Asenjo, M. Benavides, I. Herruzo, A. Revert, E. Arana, V. M. Pérez-García
Projects
- Establishing a non-invasive approach to accurately diagnose and assess brain tumors
Canadian Cancer Society (2024 - 2027) - Improving New Therapies in Oncology and Related Fields using mathematical models and biomedical data
Ministry of Science and Innovation (National Research Plan) (2023 - 2026) - Mathematical models for the digital transition in neuro-oncology: In-silico design of a clinical trial for glioblastoma.
Ministerio de Ciencia e Innovación (NextGenerationEU) (2023 - 2024) - Validation and transfer of oncological data and biomarkers based on mathematical models (AFTERbioMATH)
Ministry of Science and Innovation (Spain), Proof of Concept Program (2023 - 2024) - Mathematical models in Oncology
Ministerio de Ciencia e Innovación (Spain) (2020 - 2023)
