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 ResearchMeSH KeywordsAgedBreast NeoplasmsFemaleHealth Records, PersonalHumansMachine LearningMiddle AgedRisk AssessmentROC CurveConceptsBreast 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
2018
Development and Validation of a Multiparameterized Artificial Neural Network for Prostate Cancer Risk Prediction and Stratification
Roffman DA, Hart GR, Leapman MS, Yu JB, Guo FL, Ali I, Deng J. Development and Validation of a Multiparameterized Artificial Neural Network for Prostate Cancer Risk Prediction and Stratification. JCO Clinical Cancer Informatics 2018, 2: 1-10. PMID: 30652591, PMCID: PMC6873987, DOI: 10.1200/cci.17.00119.Peer-Reviewed Original ResearchConceptsProstate Cancer Risk PredictionCancer risk predictionPositive predictive valueProstate cancerRisk predictionPredictive valueHistory of strokeHigh-risk subgroupsBody mass indexCancer risk stratificationHealth informationPersonal health informationPrimary prostate cancerYears of ageDiabetes statusRisk stratificationSmoking statusMass indexCancer populationHeart diseaseExercise habitsCancer riskHigh riskCutoff valueAdult survey dataA multi-parameterized artificial neural network for lung cancer risk prediction
Hart GR, Roffman DA, Decker R, Deng J. A multi-parameterized artificial neural network for lung cancer risk prediction. PLOS ONE 2018, 13: e0205264. PMID: 30356283, PMCID: PMC6200229, DOI: 10.1371/journal.pone.0205264.Peer-Reviewed Original ResearchConceptsLung cancer risk predictionHistory of strokeNon-invasive clinical toolLung cancer riskHealth informationPersonal health informationNon-cancer casesCancer risk predictionRisk stratificationSmoking statusHeart diseaseExercise habitsHispanic ethnicityLung cancer detectionCancer riskClinical toolAdult dataRisk predictionModest sensitivityCancer detectionAUCHigh specificitySpecificityHypertensionAsthma
2015
Concomitant Imaging Dose and Cancer Risk in Image Guided Thoracic Radiation Therapy
Zhang Y, Wu H, Chen Z, Knisely JP, Nath R, Feng Z, Bao S, Deng J. Concomitant Imaging Dose and Cancer Risk in Image Guided Thoracic Radiation Therapy. International Journal Of Radiation Oncology • Biology • Physics 2015, 93: 523-531. PMID: 26460994, DOI: 10.1016/j.ijrobp.2015.06.034.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAge FactorsAgedAged, 80 and overAorta, ThoracicBody SizeBreastChildChild, PreschoolCone-Beam Computed TomographyFemaleHeartHumansLungMaleMiddle AgedMonte Carlo MethodOrgans at RiskPhantoms, ImagingPhotonsPrecision MedicineProtonsRadiation DosageRadiography, ThoracicRadiotherapy, Image-GuidedRisk AssessmentSex FactorsSpinal CordThoracic WallThoraxConceptsConcomitant imaging doseThoracic radiation therapyCancer riskRadiation therapyMean dosesCardiac substructuresKilovoltage cone-beamImaging doseAdverse eventsPediatric patientsMedian dosesCancer patientsRight ventricleExtra radiation doseSpinal cordHigh dosesPatientsCone beamPlanning CT imagesChest dimensionsDosesPatient sizeImaging guidanceTherapyDose