2024
Ablation Study of Diffusion Model with Transformer Backbone for Low-count PET Denoising
Huang Y, Liu X, Miyazaki T, Omachi S, Fakhri G, Ouyang J. Ablation Study of Diffusion Model with Transformer Backbone for Low-count PET Denoising. 2011 IEEE Nuclear Science Symposium Conference Record 2024, 00: 1-2. PMID: 39445309, PMCID: PMC11497477, DOI: 10.1109/nss/mic/rtsd57108.2024.10655179.Peer-Reviewed Original ResearchIR tasksImage restorationImage super-resolution taskField of image restorationSuper-resolution taskLatent feature spaceConventional UNetDenoising iterationDenoising taskTransformer backboneDenoising AutoencoderTexture restorationVision TransformerFeature spaceAblation studiesLearning schemeBackbone networkImage generationDenoisingUNetIR modelPSNRSpatial informationAutoencoderTask
2023
MedCPT: Contrastive Pre-trained Transformers with large-scale PubMed search logs for zero-shot biomedical information retrieval
Jin Q, Kim W, Chen Q, Comeau D, Yeganova L, Wilbur W, Lu Z. MedCPT: Contrastive Pre-trained Transformers with large-scale PubMed search logs for zero-shot biomedical information retrieval. Bioinformatics 2023, 39: btad651. PMID: 37930897, PMCID: PMC10627406, DOI: 10.1093/bioinformatics/btad651.Peer-Reviewed Original ResearchConceptsInformation retrievalIR tasksUser click logsSemantic information retrievalBiomedical information retrievalBiomedical knowledge acquisitionPre-trained TransformerClinical decision supportClick logsSearch logsContrastive learningLexical matchingArt performanceIR systemsSemantic retrievalBiomedical articlesDecision supportSentence representationModel encoderKnowledge acquisitionLarge modelsSemantic evaluationRetrievalTransformer modelUnprecedented scale
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