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These patient-specific computational forecasts have been regarded as a promising approach to personalize the clinical management of cancer and derive optimal treatment plans for individual patients, which constitute timely and critical needs in clinical oncology. However, the computer simulation of the underlying spatiotemporal models can entail a prohibitive computational cost, which constitutes a barrier to the successful development of clinically-actionable computational technologies for personalized tumor forecasting. To address this issue, here we propose to utilize dynamic-mode decomposition (DMD) to construct a low-dimensional representation of cancer models and accelerate their simulation. DMD is an unsupervised machine learning method based on the singular value decomposition that has proven useful in many applications as both a predictive and a diagnostic tool. We show that DMD may be applied to Fisher\u2013Kolmogorov models, which constitute an established formulation to represent untreated solid tumor growth that can further accommodate other relevant cancer phenomena (e.g., therapeutic effects, mechanical deformation). Our results show that a DMD implementation of this model over a clinically relevant parameter space can yield promising predictions, with short to medium-term errors remaining under 1% and long-term errors remaining under 20%, despite very short training periods. In particular, we have found that, for moderate to high tumor cell diffusivity and low to moderate tumor cell proliferation rate, DMD reconstructions provide accurate, bounded-error reconstructions for all tested training periods. Additionally, we also show that the three-dimensional DMD reconstruction of the tumor field can be leveraged to accurately reconstruct the displacement fields of the tumor-induced deformation of the host tissue. Thus, we posit the proposed data-driven approach has the potential to greatly reduce the computational overhead of personalized simulations of cancer models, thereby facilitating tumor forecasting, parameter identification, uncertainty quantification, and treatment optimization.<\/jats:p>","DOI":"10.1115\/1.4054925","type":"journal-article","created":{"date-parts":[[2022,6,30]],"date-time":"2022-06-30T14:20:21Z","timestamp":1656598821000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":13,"title":["Data-Driven Simulation of Fisher\u2013Kolmogorov Tumor Growth Models Using Dynamic Mode Decomposition"],"prefix":"10.1115","volume":"144","author":[{"given":"Alex","family":"Viguerie","sequence":"first","affiliation":[{"name":"Department of Mathematics, Gran Sasso Science Institute , Viale Francesco Crispi 7, L'Aquila, AQ 67100, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mal\u00fa","family":"Grave","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, COPPE\/Federal University of Rio de Janeiro , P.O. Box 68506, Rio de Janeiro, RJ 21945-970, Brazil ; , Rua Waldemar Falc\u00e3o 121, Salvador, BA 40296-710, Brazil"},{"name":"Funda\u00e7\u00e3o Oswaldo Cruz \u2013 Fiocruz , P.O. Box 68506, Rio de Janeiro, RJ 21945-970, Brazil ; , Rua Waldemar Falc\u00e3o 121, Salvador, BA 40296-710, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gabriel F.","family":"Barros","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, COPPE\/Federal University of Rio de Janeiro , P.O. Box 68506, Rio de Janeiro, RJ 21945-970, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guillermo","family":"Lorenzo","sequence":"additional","affiliation":[{"name":"Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin , 201 East 24th Street, Austin, TX 78712-1229 ; , Via Ferrata 3, Pavia, PV 27100, Italy"},{"name":"Dipartimento di Ingegneria Civile ed Architettura, Universit\u00e0 di Pavia , 201 East 24th Street, Austin, TX 78712-1229 ; , Via Ferrata 3, Pavia, PV 27100, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessandro","family":"Reali","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Civile ed Architettura, Universit\u00e0 di Pavia , Via Ferrata 3, Pavia, PV 27100, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alvaro L. G. 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