2023
Screening for extranodal extension in HPV-associated oropharyngeal carcinoma: evaluation of a CT-based deep learning algorithm in patient data from a multicentre, randomised de-escalation trial
Kann B, Likitlersuang J, Bontempi D, Ye Z, Aneja S, Bakst R, Kelly H, Juliano A, Payabvash S, Guenette J, Uppaluri R, Margalit D, Schoenfeld J, Tishler R, Haddad R, Aerts H, Garcia J, Flamand Y, Subramaniam R, Burtness B, Ferris R. Screening for extranodal extension in HPV-associated oropharyngeal carcinoma: evaluation of a CT-based deep learning algorithm in patient data from a multicentre, randomised de-escalation trial. The Lancet Digital Health 2023, 5: e360-e369. PMID: 37087370, PMCID: PMC10245380, DOI: 10.1016/s2589-7500(23)00046-8.Peer-Reviewed Original ResearchConceptsExtranodal extensionOropharyngeal carcinomaShort-axis diameterChallenging cohortPathology reportsECOG-ACRIN Cancer Research GroupDe-escalation trialsCancer Research GroupDe-escalation strategiesSurgical pathology reportsNational Cancer InstituteInter-reader agreementLargest short-axis diameterPostoperative chemoradiationProtocol exclusionsConcurrent chemoradiationPrimary endpointMulticentre trialPretreatment CTAdjuvant strategiesHuman papillomavirusTreatment selection toolUS National InstitutesPretreatment identificationStudy protocolDeveloping Validated Tools to Identify Pulmonary Embolism in Electronic Databases: Rationale and Design of the PE-EHR+ Study
Bikdeli B, Lo Y, Khairani C, Bejjani A, Jimenez D, Barco S, Mahajan S, Caraballo C, Secemsky E, Klok F, Hunsaker A, Aghayev A, Muriel A, Wang Y, Hussain M, Appah-Sampong A, Lu Y, Lin Z, Aneja S, Khera R, Goldhaber S, Zhou L, Monreal M, Krumholz H, Piazza G. Developing Validated Tools to Identify Pulmonary Embolism in Electronic Databases: Rationale and Design of the PE-EHR+ Study. Thrombosis And Haemostasis 2023, 123: 649-662. PMID: 36809777, PMCID: PMC11200175, DOI: 10.1055/a-2039-3222.Peer-Reviewed Original ResearchConceptsElectronic health recordsNLP algorithmNatural language processing toolsLanguage processing toolsPrincipal discharge diagnosisICD-10 codesDischarge diagnosisNLP toolsChart reviewHealth systemProcessing toolsYale New Haven Health SystemPatient identificationElectronic databasesHealth recordsData validationHigh-risk PEPulmonary Embolism ResearchSecondary discharge diagnosisIdentification of patientsManual chart reviewNegative predictive valueCodeRadiology reportsAlgorithm
2017
Risk of Clinically Significant Prostate Cancer Associated With Prostate Imaging Reporting and Data System Category 3 (Equivocal) Lesions Identified on Multiparametric Prostate MRI.
Sheridan AD, Nath SK, Syed JS, Aneja S, Sprenkle PC, Weinreb JC, Spektor M. Risk of Clinically Significant Prostate Cancer Associated With Prostate Imaging Reporting and Data System Category 3 (Equivocal) Lesions Identified on Multiparametric Prostate MRI. American Journal Of Roentgenology 2017, 210: 347-357. PMID: 29112469, DOI: 10.2214/ajr.17.18516.Peer-Reviewed Original ResearchConceptsCategory 3 lesionsData System (BI-RADS) category 3 lesionsPI-RADS category 3 lesionsMultiparametric prostate MRIRisk factorsProstate Imaging ReportingProstate MRIAbnormal digital rectal examination findingsPredictive valueImaging ReportingDigital rectal examination findingsClinically Significant Prostate CancerMultivariate logistic regression modelPI-RADS category 3Smaller prostate volumePI-RADS version 2Older patient ageRectal examination findingsMore risk factorsRisk stratification algorithmMRI-ultrasound fusionSignificant prostate cancerNegative predictive valuePositive predictive valueLogistic regression models