2024
Digital twins for health: a scoping review
Katsoulakis E, Wang Q, Wu H, Shahriyari L, Fletcher R, Liu J, Achenie L, Liu H, Jackson P, Xiao Y, Syeda-Mahmood T, Tuli R, Deng J. Digital twins for health: a scoping review. Npj Digital Medicine 2024, 7: 77. PMID: 38519626, PMCID: PMC10960047, DOI: 10.1038/s41746-024-01073-0.Peer-Reviewed Original Research
2023
A generalizable new figure of merit for dose optimization in dual energy cone beam CT scanning protocols
Li C, Zhou L, Deng J, Wu H, Wang R, Wang F, Yao K, Chen C, Niu T, Zhang Y. A generalizable new figure of merit for dose optimization in dual energy cone beam CT scanning protocols. Physics In Medicine And Biology 2023, 68: 185021. PMID: 37619587, DOI: 10.1088/1361-6560/acf3cd.Peer-Reviewed Original ResearchLiver cancer risk quantification through an artificial neural network based on personal health data
Ataei A, Deng J, Muhammad W. Liver cancer risk quantification through an artificial neural network based on personal health data. Acta Oncologica 2023, 62: 495-502. PMID: 37211681, DOI: 10.1080/0284186x.2023.2213445.Peer-Reviewed Original ResearchConceptsNational Health Interview SurveyLiver cancer riskHealth dataCancer riskHealth Interview SurveyHepatocellular carcinomaPersonal health dataHigh-risk populationLiver cancerInterview SurveyReceiver operating characteristic curveArea under the receiver operating characteristic curveCancer-related deathsPrimary liver cancerHealthOvarian cancerTherapeutic optionsMalignant diseaseTest cohortEarly detectionAggressive progressionRiskCancerCharacteristic curveLiverDigital Twins for Radiation Oncology
Jensen J, Deng J. Digital Twins for Radiation Oncology. 2023, 989-993. DOI: 10.1145/3543873.3587688.Peer-Reviewed Original ResearchDigital twin technologyDigital twinTwin technologyDigital twin networkModern cryptographic techniquesClinical decision-making supportDecision-making supportCryptographic techniquesVirtual clinical trialsTwin networkConventional machineGeneralized architectureFuture scientific advancesNatural applicationModeling techniquesPatient dataTechnologyMultiple institutionsLarge numberArchitectureMachineMultiscale modeling techniqueNetworkApplicationsTechniqueInternational Workshop on Digital Twins for Smart Health
Deng J, Ding Y, Achenie L, Liu J, Pan S, Purushotham S, Wu H, Wang Q. International Workshop on Digital Twins for Smart Health. 2023, 988-988. DOI: 10.1145/3543873.3589752.Peer-Reviewed Original ResearchLong-term survival and second malignant tumor prediction in pediatric, adolescent, and young adult cancer survivors using Random Survival Forests: a SEER analysis
Zhang I, Hart G, Qin B, Deng J. Long-term survival and second malignant tumor prediction in pediatric, adolescent, and young adult cancer survivors using Random Survival Forests: a SEER analysis. Scientific Reports 2023, 13: 1911. PMID: 36732358, PMCID: PMC9894907, DOI: 10.1038/s41598-023-29167-x.Peer-Reviewed Original ResearchConceptsYoung adult cancer survivorsAdult cancer survivorsRandom survival forestCancer survivorsFirst diagnosisFirst tumor diagnosisHigh-risk individualsProportional hazards modelAverage C-indexU.S. Surveillance EpidemiologyLong-term survivalTime-dependent areaTime-dependent AUCPotential clinical valueSurvival analysis studyMalignancy prediction modelSurvival forestsSEER analysisSecond malignanciesSurveillance EpidemiologySecond tumorC-indexConcordance indexClinical valuePhysician burdenStatistical 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 researchPatientsTracing and Forecasting Metabolic Indices of Cancer Patients Using Patient-Specific Deep Learning Models
Hou J, Deng J, Li C, Wang Q. Tracing and Forecasting Metabolic Indices of Cancer Patients Using Patient-Specific Deep Learning Models. Journal Of Personalized Medicine 2022, 12: 742. PMID: 35629164, PMCID: PMC9147215, DOI: 10.3390/jpm12050742.Peer-Reviewed Original ResearchShort-term memory recurrent neural networkLong short-term memory recurrent neural networkTransfer learningRecurrent neural networkDeep learning modelsReduced training timeNeural networkLearning modelTraining timeDynamical system modelLearningShort-term predictionNormsMore cancer patientsComparable levelsPhysiological modelPatient-specific modelsEditorial: Artificial Intelligence for Precision Medicine
Deng J, Hartung T, Capobianco E, Chen JY, Emmert-Streib F. Editorial: Artificial Intelligence for Precision Medicine. Frontiers In Artificial Intelligence 2022, 4: 834645. PMID: 35128393, PMCID: PMC8814648, DOI: 10.3389/frai.2021.834645.Peer-Reviewed Original ResearchEditorial: Big Data Analytics for Precision Health and Prevention
Capobianco E, Deng J. Editorial: Big Data Analytics for Precision Health and Prevention. Frontiers In Big Data 2022, 4: 835353. PMID: 35098115, PMCID: PMC8790041, DOI: 10.3389/fdata.2021.835353.Peer-Reviewed Original Research
2020
Population-Based Screening for Endometrial Cancer: Human vs. Machine Intelligence
Hart GR, Yan V, Huang GS, Liang Y, Nartowt BJ, Muhammad W, Deng J. Population-Based Screening for Endometrial Cancer: Human vs. Machine Intelligence. Frontiers In Artificial Intelligence 2020, 3: 539879. PMID: 33733200, PMCID: PMC7861326, DOI: 10.3389/frai.2020.539879.Peer-Reviewed Original ResearchAverage-risk womenEndometrial cancerRisk womenOvarian Cancer Screening TrialEndometrial cancer riskCancer Screening TrialPrimary care physiciansPopulation-based screeningCancer risk predictionHealth dataCare physiciansGynecologic oncologistsRisk stratificationDisease onsetPositive rateIndividual patientsCancer riskInvasive proceduresScreening TrialPersonal health dataEarly cancer detectionMortality rateEarly screeningFalse positive ratePrevious risk modelsA Preliminary Simulation Study of Dose-Guided Adaptive Radiotherapy Based on Halcyon MV Cone-Beam CT Images With Retrospective Data From a Phase II Clinical Trial
Huang Y, Wang H, Li C, Hu Q, Liu H, Deng J, Li W, Wang R, Wu H, Zhang Y. A Preliminary Simulation Study of Dose-Guided Adaptive Radiotherapy Based on Halcyon MV Cone-Beam CT Images With Retrospective Data From a Phase II Clinical Trial. Frontiers In Oncology 2020, 10: 574889. PMID: 33134173, PMCID: PMC7550711, DOI: 10.3389/fonc.2020.574889.Peer-Reviewed Original ResearchPhase II clinical trialEvaluation patientsClinical trialsAnatomic changesAdaptive radiotherapyPlanning CTPreliminary clinical dataMVCBCT imagesCone-beam CT imagesTarget dose coverageDeformable image registrationClinical dataDose coverageCT imagesPatientsTarget underdosageFractional doseRetrospective dataTumor siteAdaptive plansDoseCTTarget coverageLocal gamma analysisTrialsImpact of radiation source activity on short- and long-term outcomes of cervical carcinoma patients treated with high-dose-rate brachytherapy: A retrospective cohort study
Li C, Li X, You J, Liang B, Su X, Huang Y, Chen Y, Hu Q, Deng J, Wang H, Pu Y, Liu H, Ma Y, Wang W, Wu H, Zhang Y. Impact of radiation source activity on short- and long-term outcomes of cervical carcinoma patients treated with high-dose-rate brachytherapy: A retrospective cohort study. Gynecologic Oncology 2020, 159: 365-372. PMID: 32933759, DOI: 10.1016/j.ygyno.2020.08.037.Peer-Reviewed Original ResearchConceptsMetastatic recurrence-free survivalLocal recurrence-free survivalCervical carcinoma patientsRecurrence-free survivalLong-term outcomesCarcinoma patientsPatient outcomesRetrospective cohort studyShort-term outcomesMedian followCohort studyIridium-192 sourceSubgroup analysisSurvival timeRate brachytherapyStage IDay 199PatientsRadiomics at a Glance: A Few Lessons Learned from Learning Approaches
Capobianco E, Deng J. Radiomics at a Glance: A Few Lessons Learned from Learning Approaches. Cancers 2020, 12: 2453. PMID: 32872466, PMCID: PMC7563283, DOI: 10.3390/cancers12092453.Peer-Reviewed Original ResearchMedical image featuresData analyticsDeep learningMedical imagesImage featuresPrediction taskLearning methodsLearning approachComplex taskHybrid learningInference approachLarge volumesRadiomicsTaskLearningImagesAnalyticsScalabilityUltimate goalMachineAlgorithmClassificationAccuracyProcessingOptimizationPractice patterns and recommendations for pediatric image‐guided radiotherapy: A Children's Oncology Group report
Hua C, Vern‐Gross T, Hess CB, Olch AJ, Alaei P, Sathiaseelan V, Deng J, Ulin K, Laurie F, Gopalakrishnan M, Esiashvili N, Wolden SL, Krasin MJ, Merchant TE, Donaldson SS, FitzGerald TJ, Constine LS, Hodgson DC, Haas‐Kogan D, Mahajan A, Laack NN, Marcus KJ, Taylor PA, Ahern VA, Followill DS, Buchsbaum JC, Breneman JC, Kalapurakal JA. Practice patterns and recommendations for pediatric image‐guided radiotherapy: A Children's Oncology Group report. Pediatric Blood & Cancer 2020, 67: e28629. PMID: 32776500, PMCID: PMC7774502, DOI: 10.1002/pbc.28629.Peer-Reviewed Original ResearchConceptsChildren's Oncology GroupImage-guided radiotherapyOncology GroupPractice patternsOncology disciplinesChildren's Oncology Group reportPaediatric radiotherapy patientsTreatment modalitiesExpert guidelinesDose reductionRadiotherapy patientsPractice recommendationsSetup correctionAdaptive therapyRadiotherapyImage guidanceReportMember surveyGroup ReportPatientsTherapyCliniciansA general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation
Liang Y, Muhammad W, Hart GR, Nartowt BJ, Chen ZJ, Yu JB, Roberts KB, Duncan JS, Deng J. A general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation. Scientific Reports 2020, 10: 9808. PMID: 32555530, PMCID: PMC7300009, DOI: 10.1038/s41598-020-66844-7.Peer-Reviewed Original ResearchConceptsPhoton transportBoundary crossing algorithmMonte Carlo particle transport codeMonte Carlo methodTransport simulationsAcceptance-rejection samplingRadiotherapy dose calculationsPhoto-electric effectParticle transport codeEGSnrc simulationsCarlo methodBremsstrahlung eventsInelastic scatteringPair productionRayleigh scatteringThread divergenceMC simulationsTransport codeMC codeHistory schemeParticle transportCrossing algorithmInverseElectron transportSimulation accuracyRobust Machine Learning for Colorectal Cancer Risk Prediction and Stratification
Nartowt BJ, Hart GR, Muhammad W, Liang Y, Stark GF, Deng J. Robust Machine Learning for Colorectal Cancer Risk Prediction and Stratification. Frontiers In Big Data 2020, 3: 6. PMID: 33693381, PMCID: PMC7931964, DOI: 10.3389/fdata.2020.00006.Peer-Reviewed Original ResearchArtificial neural networkNeural networkOne-hot encodingSupport vector machineNational Health Interview SurveyExpectation maximization imputationNaive BayesSupervised machineRobust machineVector machineRandom forestDecision treeCRC riskColorectal cancerPLCO datasetMachineScreening datasetsNetworkColorectal cancer risk predictionImputation methodsPrevention of CRCDatasetHealth Interview SurveyListwise deletionMethod combinationMonte Carlo simulation of coherently scattered photons based on the inverse‐sampling technique
Muhammad W, Liang Y, Hart GR, Nartowt BJ, Deng J. Monte Carlo simulation of coherently scattered photons based on the inverse‐sampling technique. Acta Crystallographica Section A: Foundations And Advances 2020, 76: 70-78. PMID: 31908350, PMCID: PMC7045906, DOI: 10.1107/s2053273319014530.Peer-Reviewed Original ResearchComputational efficiencyAnomalous scattering factorsAtomic form factorsAcceptance-rejection techniqueScattering factorsMonte Carlo simulation packageMonte Carlo simulationsMonte Carlo packageAngular distributionsElastic scattering modelMonte Carlo modelTheoretical resultsSimulation algorithmMatrix calculationCarlo simulationsAnomalous scattering effectCarlo modelComplex systemsParticle transportForm factorsScattering modelSimulation accuracySimulation packageCoherent scatteringScattering effect
2019
Predicting breast cancer risk using personal health data and machine learning models
Stark GF, Hart GR, Nartowt BJ, Deng J. Predicting breast cancer risk using personal health data and machine learning models. PLOS ONE 2019, 14: e0226765. PMID: 31881042, PMCID: PMC6934281, DOI: 10.1371/journal.pone.0226765.Peer-Reviewed Original ResearchConceptsBreast cancer riskBreast cancer risk predictionCancer riskCancer risk predictionGail modelBreast cancer risk prediction toolsCancer risk prediction toolsPositive breast cancer casesHormone replacement therapyRisk stratification toolRisk predictionRisk prediction toolsHealth dataBreast cancer casesPersonal health dataStratification toolReplacement therapyLeading causeBreast cancerCancer casesInvasive proceduresBCRATDeLong testLogistic regressionEarly breast cancer detection