2023
Developing 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 reportsAlgorithmBladder Cancer Radiation Oncology of the Future: Prognostic Modelling, Radiomics, and Treatment Planning With Artificial Intelligence
Moore N, McWilliam A, Aneja S. Bladder Cancer Radiation Oncology of the Future: Prognostic Modelling, Radiomics, and Treatment Planning With Artificial Intelligence. Seminars In Radiation Oncology 2023, 33: 70-75. PMID: 36517196, DOI: 10.1016/j.semradonc.2022.10.009.Peer-Reviewed Original ResearchConceptsArtificial intelligenceMachine learningReliability of algorithmAccurate predictive modelsEfficient creationIntelligenceBladder cancer patientsRadiation oncology patientsAlgorithmPrognostic modellingRoutine clinical useClinical outcomesOncology patientsClinical recordsCancer patientsBladder cancerPredictive modelTreatment planClinical useMultiple treatment plansClinical implementationNext stepRadiation oncologyTreatment planningInterpretability
2019
Applications of artificial intelligence in neuro-oncology.
Aneja S, Chang E, Omuro A. Applications of artificial intelligence in neuro-oncology. Current Opinion In Neurology 2019, 32: 850-856. PMID: 31609739, DOI: 10.1097/wco.0000000000000761.Peer-Reviewed Original ResearchConceptsArtificial intelligenceArtificial intelligence algorithmsNatural language processingAmount of dataIntelligence algorithmsLanguage processingIntelligenceNeuro-oncologyImage analysisApplicationsAlgorithmRisk stratificationFuture innovationsTreatment responseBrain tumorsClinical practiceClassificationRecent applicationsProcessingSignificant promiseChallengesDetection