Alamán-Díez, P., Borau, C., Guerrero, P. E., Amaveda, H., Mora, M., Fraile, J. M., & Pérez, M. Á, Collagen-Laponite Nanoclay Hydrogels for Tumor Spheroid Growth, Biomacromolecules https://pubs.acs.org/doi/10.1021/acs.biomac.3c00257 

Gonçalves IG; Hormuth II DA; Prabhakaran S; Phillips CM; García-Aznar JM,Supporting data for “PhysiCOOL: A generalized framework for model Calibration and Optimization Of modeLing projects”, GigaByte 10.46471/gigabyte.77

Silvia Hervas-Raluy; Barbara Wirthl; Pedro E. Guerrero; Gil Robalo Rei; Jonas Nitzler; Esther Coronado; Jaime Font de Mora Sainz; Bernhard A. Schrefler; Maria Jose Gomez-Benito; Jose Manuel Garcia-Aznar; Wolfgang A. Wall, Tumour growth: An approach to calibrate parameters of a multiphase porous media model based on in vitro observations of Neuroblastoma spheroid growth in a hydrogel microenvironment 10.1016/j.compbiomed.2023.106895

Haridimos Kondylakis; Varvara Kalokyri; Stelios Sfakianakis; Kostas Marias; Manolis Tsiknakis; Ana Jimenez-Pastor; Eduardo Camacho-Ramos; Ignacio Blanquer; J. Damian Segrelles; Sergio López-Huguet; Caroline Barelle; Magdalena Kogut-Czarkowska; Gianna Tsakou; Nikolaos Siopis; Zisis Sakellariou; Paschalis Bizopoulos; Vicky Drossou; Antonios Lalas; Konstantinos Votis; Pedro Mallol; Luis Marti-Bonmati; Leonor Cerdá Alberich; Karine Seymour; Samuel Boucher; Esther Ciarrocchi; Lauren Fromont; Jordi Rambla; Alexander Harms; Andrea Gutierrez; Martijn P. A. Starmans; Fred Prior; Josep Ll. Gelpi; Karim Lekadir, A report on the experiences of five EU projects, European Radiology Experimental, 10.1186/s41747-023-00336-x, https://doi.org/10.1186/s41747-023-00336-x

Daniel Navajas; José Manuel Garcia-Aznar; Gabriel Beltran, Mechanical modeling of lung alveoli: From macroscopic behaviour to cell mechano-sensing at microscopic level, Journal of the Mechanical Behavior of Biomedical Materials, 10.1016/j.jmbbm.2021.105043,  https://doi.org/10.1016/j.jmbbm.2021.105043

Kondylakis, Haridimos; Ciarrocchi, Esther; Cerda-Alberich, Leonor; Chouvarda, Ioanna; Fromont, Lauren A.; Garcia-Aznar, Jose Manuel; Kalokyri, Varvara; Kosvyra, Alexandra; Walker, Dawn; Yang, Guang; Neri, Emanuele; The AI4HealthImaging Working Group on metadata models, Position of the AI for Health Imaging (AI4HI) network on metadata models for imaging biobanks, European Radiology Experimental, 10.1186/s41747-022-00281-1, https://doi.org/10.1186/s41747-022-00281-1

Leonor Cerdá-Alberich; Jimena Solana; Pedro Mallol; Gloria Ribas; Miguel García-Junco; Angel Alberich-Bayarri; Luis Marti-Bonmati, MAIC–10 brief quality checklist for publications using artificial intelligence and medical images, Insights into Imaging, 10.1186/s13244-022-01355-9, https://doi.org/10.1186/s13244-022-01355-9

Daniel Camacho-Gómez; José Manuel García-Aznar; María José Gómez-Benito, A 3D multi-agent-based model for lumen morphogenesis: the role of the biophysical properties of the extracellular matrix, Engineering with computers, 10.1007/s00366-022-016541,  https://pubmed.ncbi.nlm.nih.gov/36397878

Gonçalves, Inês G.; García-Aznar, José Manuel, Hybrid computational models of multicellular tumour growth considering glucose metabolism, Computational and Structural Biotechnology Journal, 10.1016/j.csbj.2023.01.044, http://zaguan.unizar.es/record/125288

Varella, Vinicius, Orchestration of multiscale models for computational oncolhttps://zenodo.org/record/8025198ogy, 10.5281/zenodo.8025198, https://zenodo.org/record/8025198

Francisco Merino-Casallo; Maria Jose Gomez-Benito; Silvia Hervas-Raluy; Jose Manuel Garcia-Aznar, Unravelling cell migration: defining movement from the cell surface, Cell Adhesion &  Migration, 10.1080/19336918.2022.2055520, https://doi.org/10.1080/19336918.2022.2055520

Luis Marti-Bonmati; Dow-Mu Koh; Katrine Riklund; Maciej Bobowicz; Yiannis Roussakis; Joan C. Vilanova; Jurgen J. Fütterer; Jordi Rimola; Pedro Mallol; Gloria Ribas; Ana Miguel; Manolis Tsiknakis; Karim Lekadir; Gianna Tsakou, Considerations for artificial intelligence clinical impact in oncologic imaging: an AI4HI position paper, Insights Into Imaging, 10.1186/s13244-022-01220-9, https://fundanet.iislafe.san.gva.es/publicaciones/ProdCientif/PublicacionFrw.aspx?id=15928

Francisco Merino-Casallo; Maria Jose Gomez-Benito; Ruben Martinez-Cantin; Jose Manuel Garcia-Aznar, A mechanistic protrusive-based model for 3D cell migration, European Journal of Cell Biology, 10.1016/j.ejcb.2022.151255, http://zaguan.unizar.es/record/118092

Hervas-Raluy, Silvia; Sainz de Mena, Diego; Gómez Benito, Mª José; García-Aznar, José Manuel, Herramienta de apoyo para cáncer pediátrico, Jornada De Jóvenes Investigadores E Investigadoras Del I3A, 10.26754/jjii3a.20226993,  https://doi.org/10.26754/jjii3a.20226993

Bárbara de Melo Quintela, Silvia Hervas-Raluy, Jose Manuel Garcia-Aznar, Dawn Walker, Kenneth Y. Wertheim, Marco Viceconti, A theoretical analysis of the scale separation in a model to predict solid tumour growth, Journal of Theoretical Biology

Italia, M.; Wertheim, K.Y.; Taschner-Mandl, S.; Walker, D.; Dercole, F., Mathematical Model of Clonal Evolution Proposes a Personalised Multi-Modal Therapy for High-Risk Neuroblastoma, Cancers, 10.3390/cancers15071986

Paul Richmond, Robert Chisholm, Peter Heywood, Mozhgan Kabiri Chimeh, Matthew Leach, FLAME GPU 2: A framework for flexible and performant agent based simulation on GPUs, Software: Practice and Experience, 10.1002/spe.3207

Diana Veiga-Canuto, Leonor Cerdà-Alberich, Ana Jiménez-Pastor, José Miguel Carot Sierra, Armando Gomis-Maya, Cinta Sangüesa-Nebot, Matías Fernández-Patón, Blanca Martínez de las Heras, Sabine Taschner-Mandl, Vanessa Düster, Ulrike Pötschger, Thorsten Simon, Emanuele Neri,Ángel Alberich-Bayarri, Adela Cañete, Barbara Hero, Ruth Ladenstein, Luis Martí-Bonmatí, Independent Validation of a Deep Learning nnU-Net Tool for Neuroblastoma Detection and Segmentation in MR Images in Cancers (2023) https://doi.org/10.3390/cancers15051622

Wolfgang Jentner, Giuliana Lindholz, Hanna Hauptmann, Mennatallah El-Assady, Kwan-Liu Ma, Daniel A. Keim, Visual Analytics of Co-Occurrences to Discover Subspaces in Structured Data in ACM Transactions on Interactive Intelligent Systems (2023) https://dl.acm.org/doi/10.1145/3579031

Diego Sainz-DeMena, José Manuel García-Aznar, María Ángeles Pérez,Carlos Borau, Im2mesh: A Python Library to Reconstruct 3D Meshes from Scattered Data and 2D Segmentations, Application to Patient-Specific Neuroblastoma Tumour Image Sequences https://doi.org/10.3390/app122211557

Damià Segrelles, Sergio López-Huguet, Pau Lozano, Ignacio Blanquer, A federated cloud architecture for processing of cancer images on a distributed storage in Future Generation Computer Systems 139(2) (2022) https://doi.org/10.1016/j.future.2022.09.019

V. Varella, B de Melo Quintela, M. Kasztelnik, and M. Viceconti, Effect of particularisation size on the accuracy and efficiency of a multiscale tumours’ growth model in International Journal for Numerical Methods in Biomedical Engineering 2022, 38(12), e3657 https://doi.org/10.1002/cnm.3657

Diana Veiga-Canuto, Comparative Multicentric Evaluation of Inter-Observer Variability in Manual and Automatic Segmentation of Neuroblastic Tumors in Magnetic Resonance Images in Cancers, 2022, 14(15), 3648 https://doi.org/10.3390/cancers14153648

Carlos Baeza-Delgado, Leonor Cerdá Alberich, José Miguel Carot-Sierra, Diana Veiga-Canuto, Blanca Martínez de las Heras, Ben Raza & Luis Martí-Bonmatí, A practical solution to estimate the sample size required for clinical prediction models generated from observational research on data (2022) 10.1186/s41747-022-00276-y

Diana Veiga-Canuto, Leonor Cerdà-Alberich, Cinta Sangüesa, Blanca Martínez de las Heras, Ulrike Pötschger, Michela Gabelloni, ORCID,José Miguel Carot Sierra, Sabine Taschner-Mandl, Vanessa Düster, Adela Cañete, Ruth Ladenstein, Emanuele Neri andLuis Martí-Bonmatí, Automatic Segmentation of Neuroblastic Tumors in Magnetic Resonance Images (2022). https://doi.org/10.3390/cancers14153648 

Sainz-DeMena, D., Ye, W., Pérez, M.Á. et al. A finite element based optimization algorithm to include diffusion into the analysis of DCE-MRI. Engineering with Computers (2022). https://doi.org/10.1007/s00366-022-01667-w

Gabelloni M, Faggioni L, Borgheresi R, et al. Bridging gaps between images and data: a systematic update on imaging biobanks [published online ahead of print, 2022 Jan 10]. Eur Radiol. 2022;10.1007/s00330-021-08431-6. doi:10.1007/s00330-021-08431-6

M. Viceconti, M. A. Juárez, C. Curreli, M. Pennisi, G. Russo and F. Pappalardo, “Credibility of In Silico Trial Technologies—A Theoretical Framing,” in IEEE Journal of Biomedical and Health Informatics, vol. 24, no. 1, pp. 4-13, Jan. 2020, doi: 10.1109/JBHI.2019.2949888.

T. Spinner, U. Schlegel, H. Schäfer and M. El-Assady, “explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning,” in IEEE Transactions on Visualization and Computer Graphics, vol. 26, no. 1, pp. 1064-1074, Jan. 2020, doi: 10.1109/TVCG.2019.2934629.

Giménez-Alventosa V, Segrelles JD, Moltó G, Roca-Sogorb M. APRICOT: Advanced Platform for Reproducible Infrastructures in the Cloud via Open Tools. Methods Inf Med. 2020;59(S 02):e33-e45, doi: 10.1055/s-0040-1712460

Buchmüller, Juri & Schlegel, Udo & Cakmak, Eren & Keim, Daniel & Dimara, Evanthia. (2021). SpatialRugs: A compact visualization of space and time for analyzing collective movement data. Computers & Graphics, doi: 10.1016/j.cag.2021.08.003.

Lucignani, Giovanni & Neri, Emanuele. (2019). Integration of imaging biomarkers into systems biomedicine: a renaissance for medical imaging. Clinical and Translational Imaging. 7, doi: 10.1007/s40336-019-00320-9.

Bubak M, Czechowicz K, Gubała T, et al. The EurValve model execution environment. Interface Focus. 2021;11(1):20200006.
https://doi.org/10.1098/rsfs.2020.0006

Nieto, A. & Escribano, Jorge & Spill, Fabian & Garcia Aznar, Jose Manuel & Gomez-Benito, Maria Jose. (2019). Finite element simulation of the structural integrity of endothelial cell monolayers: A step for tumor cell extravasation. Engineering Fracture Mechanics. 224. 106718.
https://doi.org/10.1016/j.engfracmech.2019.106718

Juste-Lanas Y, Guerrero PE, Camacho-Gómez D, Hervás-Raluy S, García-Aznar JM, Gomez-Benito MJ. Confined Cell Migration and Asymmetric Hydraulic Environments to Evaluate the Metastatic Potential of Cancer Cells. J Biomech Eng. 2022;144(7)
https://doi.org/10.1115/1.4053143

Schlegel, U., Vo, D.L., Keim, D.A., Seebacher, D. (2021). TS-MULE: Local Interpretable Model-Agnostic Explanations for Time Series Forecast Models. In: , et al. Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD 2021. Communications in Computer and Information Science, vol 1524. Springer, Cham. https://doi.org/10.1007/978-3-030-93736-2_1

U. Schlegel, D. A. Keim: Time Series Model Attribution Visualizations as Explanations. Workshop on Trust and Expertise in Visual Analytics (TREX) at IEEE Visualization Conference (VIS), 2021 https://doi.org/10.1109/TREX53765.2021.00010

Fernández Patón, M., Cerdá Alberich, L., Sangüesa Nebot, C. et al. MR Denoising Increases Radiomic Biomarker Precision and Reproducibility in Oncologic Imaging. J Digit Imaging (2021).
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Cerdá Alberich, L.; Sangüesa Nebot, C.; Alberich-Bayarri, A.; Carot Sierra, J.M.; Martínez de las Heras, B.; Veiga Canuto, D.; Cañete, A.; Martí-Bonmatí, L. A Confidence Habitats Methodology in MR Quantitative Diffusion for the Classification of Neuroblastic Tumors. Cancers 2020, 12, 3858.
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Bonmatí, L. M., Alberich-Bayarri, A., Ladenstein R., Blanquer, I, Segrelles, J.D., Cerdá-Alberich, L., … Neri, N. (2020). PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers. European Radiology Experimental 2020(4:22).
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Scapicchio, C., Gabelloni, M., Forte, S.M. et al. DICOM-MIABIS integration model for biobanks: a use case of the EU PRIMAGE project. Eur Radiol Exp 5, 20 (2021).
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Gonçalves IG, Garcia-Aznar JM (2021) Extracellular matrix density regulates the formation of tumour spheroids through cell migration. PLoS Comput Biol 17(2): e1008764. https://doi.org/10.1371/journal.pcbi.1008764