2023
Statistical biopsy: An emerging screening approach for early detection of cancers
Hart G, Yan V, Nartowt B, Roffman D, Stark G, Muhammad W, Deng J. Statistical biopsy: An emerging screening approach for early detection of cancers. Frontiers In Artificial Intelligence 2023, 5: 1059093. PMID: 36744110, PMCID: PMC9895959, DOI: 10.3389/frai.2022.1059093.Peer-Reviewed Original ResearchCancer riskDifferent cancer typesCancer typesStatistical modelRisk of complicationsIndividual cancer riskPersonal health dataHealth dataGeneral populationMultiple cancer risksBiopsyCancerContinuous outputMost cancersTraditional biopsyEarly detectionRiskBinary outputCancer detectionNeural networkMachine learningTraditional methodsMorbidityComplicationsModel
2022
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