2025
Results of a Global Survey on the State of Interventional Radiology 2024
Guan J, Elhakim T, Matsumoto M, McKeon T, Laage-Gaupp F, Iqbal S, Patel P, Pereira P, Tam A, Binkert C, Sofocleous C. Results of a Global Survey on the State of Interventional Radiology 2024. Journal Of Vascular And Interventional Radiology 2025 PMID: 39793699, DOI: 10.1016/j.jvir.2024.12.594.Peer-Reviewed Original ResearchTraining programIR training programInterventional radiologyDiagnostic radiologistsIncreasing patient awarenessAmerican training programsIR servicesSpecialty affiliationHospital settingPatient referralPatient awarenessImprove accessAnonymous surveyInterventional radiologistsMedical studentsMultidisciplinary conferenceIR exposureRadiology trainingEducational characteristicsSocietal effortsSpecialtyEducationSurveyRadiologistsAwareness
2023
Comparative Analysis of Percutaneous Drainage versus Operative Drainage of Intra-Abdominal Abscesses in a Resource-Limited Setting: The Tanzanian Experience
Ukweh O, Alswang J, Iya-Benson J, Naif A, Chan S, Laage-Gaupp F, Asch M, Ramalingam V. Comparative Analysis of Percutaneous Drainage versus Operative Drainage of Intra-Abdominal Abscesses in a Resource-Limited Setting: The Tanzanian Experience. Annals Of Global Health 2023, 89: 35. PMID: 37273489, PMCID: PMC10237249, DOI: 10.5334/aogh.4070.Peer-Reviewed Original ResearchConceptsIntra-abdominal abscessPercutaneous abscess drainageSurgical abscess drainageNational Referral HospitalTechnical success rateAbscess drainageInterventional radiologyImage-guided percutaneous abscess drainageRetrospective cohort studyHigh technical successStandard of careSuccess rateManual chart reviewResource limited settingsResource-limited settingsChart reviewCohort studyComplication rateOperative drainagePercutaneous drainageReferral hospitalClinical outcomesProcedural dataPAD groupTechnical success
2018
Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma.
Abajian A, Murali N, Savic LJ, Laage-Gaupp FM, Nezami N, Duncan JS, Schlachter T, Lin M, Geschwind JF, Chapiro J. Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma. Journal Of Visualized Experiments 2018 PMID: 30371657, PMCID: PMC6235502, DOI: 10.3791/58382.Peer-Reviewed Original ResearchConceptsIntra-arterial therapyN patientsHepatocellular carcinomaTrans-arterial therapiesIntra-arterial treatmentCohort of patientsStandard of careLikelihood of responseClinical research questionsSurgical resectionNew patientsTreatment responseUnivariate associationsPatientsTraining patientsInterventional radiologyTherapyCarcinomaTreatmentImage-guided therapyOutcomesFinal modelImaging dataResectionResponse
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