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Results: 76
Number of items: 76
  • Open Access
    Sloot, P. M. A., Quax, R., & Gu, M. (2024). Natural Information Processing. In D. C. Krakauer (Ed.), Foundational Papers in Complexity Science. - Volume 4: 1989-2000 (pp. 2447-2532). SFI Press. https://doi.org/10.37911/9781947864559.78
  • Open Access
    Uleman, J. F., Quax, R., Melis, R. J. F., Hoekstra, A. G., & Olde Rikkert, M. G. M. (2024). The need for systems thinking to advance Alzheimer's disease research. Psychiatry Research, 333, Article 115741. https://doi.org/10.1016/j.psychres.2024.115741
  • Koloi, A., Loukas, V. S., Sakellarios, A., Bosch, J. A., Quax, R., Nowakowska, K., Tachos, N., Kaźmierski, J., Papaloukas, C., & Fotiadis, D. (2023). A comparison study on creating simulated patient data for individuals suffering from chronic coronary disorders. In 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC): proceedings : Sydney, Australia, 24-27 July 2023 (pp. 3630-3633). IEEE. https://doi.org/10.1109/EMBC40787.2023.10340194
  • Open Access
    Hourican, C., Peeters, G., Melis, R. J. F., Wezeman, S. L., Gill, T. M., Olde Rikkert, M. G. M., & Quax, R. (2023). Understanding multimorbidity requires sign-disease networks and higher-order interactions, a perspective. Frontiers in Systems Biology, 3, Article 1155599. https://doi.org/10.3389/fsysb.2023.1155599
  • Open Access
    Yildirim, V., Sheraton, V. M., Brands, R., Crielaard, L., Quax, R., Riel, N. A. W. V., Stronks, K., Nicolaou, M., & Sloot, P. M. A. (2023). A data-driven computational model for obesity-driven diabetes onset and remission through weight loss. iScience, 26(11), Article 108324. https://doi.org/10.1016/j.isci.2023.108324
  • Open Access
    Uleman, J. F., Melis, R. J. F., Hoekstra, A. G., Olde Rikkert, M. G. M., Quax, R., & the Australian Imaging, Biomarker and Lifestyle study of Aging and Alzheimer's Disease Neuroimaging Initiative studies (2023). Exploring the potential impact of multi-factor precision interventions in Alzheimer's disease with system dynamics. Journal of Biomedical Informatics, 145, Article 104462. https://doi.org/10.1016/j.jbi.2023.104462
  • Open Access
    Crielaard, L., Quax, R., Sawyer, A. D. M., Vasconcelos, V. V., Nicolaou, M., Stronks, K., & Sloot, P. M. A. (2023). Using network analysis to identify leverage points based on causal loop diagrams leads to false inference. Scientific Reports, 13(1), Article 21046. https://doi.org/10.1038/s41598-023-46531-z
  • Open Access
    Rydin, A. O., Milaneschi, Y., Quax, R., Li, J., Bosch, J. A., Schoevers, R. A., Giltay, E. J., Penninx, B. W. J. H., & Lamers, F. (2023). A network analysis of depressive symptoms and metabolomics. Psychological Medicine, 53(15), 7385-7394. https://doi.org/10.1017/S0033291723001009
  • Open Access
    Gabel, A., Klein, V., Valperga, R., Lamb, J. S. W., Webster, K., Quax, R., & Gavves, E. (2023). Learning Lie Group Symmetry Transformations with Neural Networks. Proceedings of Machine Learning Research, 221, 50-59. https://proceedings.mlr.press/v221/gabel23a.html
  • Open Access
    Uleman, J. F., Melis, R. J. F., Ntanasi, E., Scarmeas, N., Hoekstra, A. G., Quax, R., Olde Rikkert, M. G. M., & Alzheimer's Disease Neuroimaging Initiative (2023). Simulating the multicausality of Alzheimer's disease with system dynamics. Alzheimer's and Dementia, 19(6), 2633-2654. https://doi.org/10.1002/alz.12923
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