2019
Development and validation of image quality scoring criteria (IQSC) for pediatric CT: a preliminary study
Padole A, Sagar P, Westra S, Lim R, Nimkin K, Kalra M, Gee M, Rehani M. Development and validation of image quality scoring criteria (IQSC) for pediatric CT: a preliminary study. Insights Into Imaging 2019, 10: 95. PMID: 31549234, PMCID: PMC6757090, DOI: 10.1186/s13244-019-0769-8.Peer-Reviewed Original ResearchCT examsVentriculoperitoneal (VP) shuntBoard-certified pediatric radiologistsMedian image quality scorePediatric CT examinationsPediatric CT examsAdequate image qualityImage quality scoresRoutine abdomenRoutine chestPediatric CTScoring criteriaCT examinationsPediatric radiologistsInterobserver agreementInterobserver variabilityAssessment of image qualityImage qualityKidney stonesVentriculoperitonealScoring scaleRadiologistsScoresExamQuality scores
2018
Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability
Tajmir S, Lee H, Shailam R, Gale H, Nguyen J, Westra S, Lim R, Yune S, Gee M, Do S. Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability. Skeletal Radiology 2018, 48: 275-283. PMID: 30069585, DOI: 10.1007/s00256-018-3033-2.Peer-Reviewed Original ResearchConceptsBone age assessmentAutomated artificial intelligenceAI assistanceBone age radiographsConvolutional neural networkDeep learning algorithmsRoot mean square errorMean square errorPediatric radiologistsUtilization of AILearning algorithmsNeural networkArtificial intelligenceIntraclass correlation coefficientImproved performancePooled cohortRadiologist interpretationImaging studiesInter-rater variationAccuracyMetabolic disordersIncreased accuracyRadiologistsAge accuracyMeasures of accuracy