2021

• Evolutionary dynamics at the tumor edge reveals metabolic imaging biomarkers. Proceedings of the National Academy of Sciences (USA) 118(6) e2018110118 (2021).
• A mesoscopic simulator to uncover heterogeneity and evolutionary dynamics in tumors. PLoS Computational Biology 17(2) e1008266 (2021).

2020

• Universal scaling laws rule explosive growth in human cancers. Nature Physics 16, 1232-1237 (2020).

2019

• Approaching the Rank Aggregation Problem by Local Search-based Metaheuristics. Journal of Computational and Applied Mathematics 354, 445-456 (2019).
• Morphologic features on MR imaging classify multifocal glioblastomas in different prognostic groups. American Journal of Neuro-radiology 40 (4) 634-640 (2019).
• Morphological MRI-based features provide pretreatment and post-surgery survival prediction in glioblastoma. European Radiology 29(4) 1968-1977 (2019).
• Prognostic models based on imaging findings in glioblastoma: Human versus Machine. Scientific Reports 9:5982 (2019).

2018

• 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).
• Tumor Surface Regularity at MR Imaging Predicts Survival and Response to Surgery in Patients with Glioblastoma. Radiology 288(1), 218-225 (2018).
• Consensus-Based Journal Rankings: A Complementary Tool for Bibliometric Evaluation. Journal of the Association for Information Science and Technology 69(7), 936-948 (2018).
• Predictive and prognostic potential of volume-based metabolic variables obtained by basal 18F-FDG PET/CT in breast cancer with neoadjuvant chemotherapy indication. Revista Española de Medicina Nuclear e Imagen Molecular 37(2), 73-79 (2018).

2017

• Tackling the supervised label ranking problem by bagging weak learners. Information Fusion 35, 38-50 (2017).
• Glioblastoma: Does the pre-treatment geometry matter? A postcontrast T1 MRI-based study. European Radiology 27(3), 1096-1104 (2017).
• Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization. PLoS One 12(6):e0178843 (2017).
• Metabolic tumor burden assessed by dual time point 18F-FDG PET/CT in locally advanced breast cancer: Relation with tumor biology. Molecular Imaging and Biology 19(4), 636-644 (2017).
• Textural features and SUV-based variables assessed by dual time point 18F-FDG PET/CT in locally advanced breast cancer.
  Annals of Nuclear Medicine 31(10) 726-735 (2017).
• 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. (2017).
• Novel geometrical imaging biomarkers predict survival and allow for patient selection for surgery in glioblastoma patients. Neuro-Oncology 19(3):iii80-iii80 (2017).
• Recommendations for computation of textural measures obtained from 3D brain tumor MRIs: A robustness analysis points out the need for standardization. Neuro-Oncology 19 (3): iii44 (2017).
• Towards individualized survival prediction in glioblastoma patients using machine learning methods. Neuro-Oncology 19(3):iii84-iii84 (2017).

2016

• Geometrical measures obtained from pretreatment postcontrast T1 weighted MRIs predict survival benefits from bevacizumab in glioblastoma patients. PLoS One 11(8) e0161484 (2016).
• Influence of grey level and space discretization on brain tumor heterogeneity measures obtained from MRIs. Computers in Biology and Medicine 78, 49-57 (2016).
• Metabolic tumor burden assessed by dual time point 18F-FDG PET/CT in breast cancer: Relation with tumor biology. European Journal of Nuclear Medicine and Molecular Imaging 43, S74-S75 (2016).
• Tumour heterogeneity in glioblastoma assessed by MRI texture analysis: a potential marker of survival. British Journal on Radiology 89, 2016242 (2016).
• Using extensión sets to aggregate partial rankings in a flexible setting. Applied Mathematics and Computation 290,208-223 (2016).
• Using metaheuristic algorithms for the parameter estimation in generalized Mallows model. Applied Soft Computing 38, 308-320 (2016).

2013

• Tackling the rank aggregation problem with evolutionary algorithms. Applied Mathematics and Computation 222, 632-644 (2013).