2024
Assessment of valve regurgitation severity via contrastive learning and multi-view video integration
Kim S, Ren H, Charton J, Hu J, Gonzalez C, Khambhati J, Cheng J, DeFrancesco J, Waheed A, Marciniak S, Moura F, Cardoso R, Lima B, McKinney S, Picard M, Li X, Li Q. Assessment of valve regurgitation severity via contrastive learning and multi-view video integration. Physics In Medicine And Biology 2024, 69: 045020. PMID: 38271727, DOI: 10.1088/1361-6560/ad22a4.Peer-Reviewed Original ResearchConceptsRepresentation learningContrastive learningMulti-view video processingState-of-the-art methodsContrastive learning frameworkState-of-the-artIn-house datasetVideo processingContrastive networkEmbedding spaceImage inputLearning frameworkVideo integrationIntricate taskLoss termMulti-modal clinical dataLearningRepresentationLabor-intensiveAccuracyEfficient methodVideo seriesEmbeddingDatasetNetwork
2020
Becoming Clinician-Animators: a Toolkit and Pilot Study for Novel Animated Content Development in a Medical Education Curriculum
Brown B, Gao C, Windish D, Moeller J, O’Neill E, Soares S. Becoming Clinician-Animators: a Toolkit and Pilot Study for Novel Animated Content Development in a Medical Education Curriculum. Medical Science Educator 2020, 30: 977-988. PMID: 34457756, PMCID: PMC8368584, DOI: 10.1007/s40670-020-00959-4.Peer-Reviewed Original ResearchMedical educationFlipped classroom curriculumMultimedia teaching toolsMedical education curriculumEffectiveness of animationGraduate Medical EducationArt of animationEducation curriculumClassroom curriculumTeaching toolInternal medicine residentsContent developmentVideo seriesEducationCurriculumCognitive theoryMedicine residentsPilot studyAnimationEducatorsAnthropomorphic charactersLearnersMultimediaEnthusiasmDialogue
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply