Work

Dataset and codes to investigate personalized computational forecasting of prostate cancer growth and progression at diagnosis

Year: 2026

Type: other

Abstract: Dataset and codes to investigate personalized computational forecasting of prostate cancer growth and progression at diagnosis

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.22088216

Authors: Davarci, Orhun O., Nandalur, Kiran R., Gomez, Hector, Reali, Alessandro, Hughes, Thomas J. R., Yankeelov, Thomas E., Lorenzo, Guillermo

Institutions: The University of Texas at Austin, Beaumont Hospital, Troy, Corewell Health Trenton Hospital, Purdue University West Lafayette, University of Pavia, Universidade da Coruña

Language: English

Topic: Mathematical Biology Tumor Growth

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: Cancer Prevention and Research Institute of Texas, European Commission, Ministero dell’Istruzione, dell’Università e della Ricerca, Agencia Estatal de Investigación

Awards: Personalised Image-based Computational Modelling Framework to Forecast Prostate Cancer, G4670997421, Recruitment of Established Investigators, XFAST-SIMS: Extra fast and accurate simulation of complex structural systems, G882206014

OpenAlex ID: W7204171727

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