Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation
Stahlberg E, Abdel-Rahman M, Aguilar B, Asadpoure A, Beckman R, Borkon L, Bryan J, Cebulla C, Chang Y, Chatterjee A, Deng J, Dolatshahi S, Gevaert O, Greenspan E, Hao W, Hernandez-Boussard T, Jackson P, Kuijjer M, Lee A, Macklin P, Madhavan S, McCoy M, Mirzaei N, Razzaghi T, Rocha H, Shahriyari L, Shmulevich I, Stover D, Sun Y, Syeda-Mahmood T, Wang J, Wang Q, Zervantonakis I. Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation. Frontiers In Digital Health 2022, 4: 1007784. PMID: 36274654, PMCID: PMC9586248, DOI: 10.3389/fdgth.2022.1007784.Peer-Reviewed Original ResearchMonitoring treatment responsePatient digital twinsUS National Cancer InstituteNational Cancer InstituteTreatment responsePlanning treatmentEarly progressionCancer preventionDigital twin approachIndividual patientsPersonalized treatmentPilot projectCancer InstituteCancer typesCancerDigital twinDeep phenotypingCancer researchPatients
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