2025
Searching for the Ideal Recipe for Preparing Synthetic Data in the Multi-Object Detection Problem
Staniszewski M, Kempski A, Marczyk M, Socha M, Foszner P, Cebula M, Labus A, Cogiel M, Golba D. Searching for the Ideal Recipe for Preparing Synthetic Data in the Multi-Object Detection Problem. Applied Sciences 2025, 15: 354. DOI: 10.3390/app15010354.Peer-Reviewed Original ResearchSynthetic dataUtilization of synthetic dataSynthetic data generation methodAdvancement of deep learning methodsSynthetic data generation techniquesReal-world datasetsLevel of photorealismDeep learning methodsDetection methodData generation techniquesData generation methodEnhanced detection methodNetwork trainingClassification qualityDetection metricsDetection problemLearning methodsTraining datasetTraining processGeneration methodData quantityGeneration techniqueMulti-objectiveTraining methodsDataset
2024
Attention-based acoustic feature fusion network for depression detection
Xu X, Wang Y, Wei X, Wang F, Zhang X. Attention-based acoustic feature fusion network for depression detection. Neurocomputing 2024, 601: 128209. DOI: 10.1016/j.neucom.2024.128209.Peer-Reviewed Original ResearchFeature fusion networkFusion networkDepression detectionAdvanced machine learning paradigmsDeep neural networksMachine learning paradigmLSTM-attention mechanismSpeech databaseFeature modelSpeech featuresNeural networkAbundance of informationBoost performanceLearning paradigmImproved detection methodAuditory dataAcoustic featuresDetection methodFeature processingAdjustment moduleNetworkLSTM-AttentionResearch directionsEffective detectionFeaturesEvaluation of few-shot detection of head and neck anatomy in CT
Lee K, Cho J, Lee J, Xing F, Liu X, Bae H, Lee K, Hwang J, Park J, Fakhri G, Jee K, Woo J. Evaluation of few-shot detection of head and neck anatomy in CT. Progress In Biomedical Optics And Imaging 2024, 12927: 1292716-1292716-7. DOI: 10.1117/12.3006895.Peer-Reviewed Original ResearchFew-shot object detection methodMedical image dataFew-shot object detectionObject detection methodsObject detectionImage dataObject detection approachState-of-the-artFaster R-CNNFine-tuning stageDeep learning modelsDetection methodFew-shotDetection of anatomical structuresDownstream tasksNatural imagesR-CNNDetect objectsDetection headDetection approachPreprocessing stepDetect anatomical structuresLearning modelsExperimental resultsClinical workflowEnsemble pretrained language models to extract biomedical knowledge from literature
Li Z, Wei Q, Huang L, Li J, Hu Y, Chuang Y, He J, Das A, Keloth V, Yang Y, Diala C, Roberts K, Tao C, Jiang X, Zheng W, Xu H. Ensemble pretrained language models to extract biomedical knowledge from literature. Journal Of The American Medical Informatics Association 2024, 31: 1904-1911. PMID: 38520725, PMCID: PMC11339500, DOI: 10.1093/jamia/ocae061.Peer-Reviewed Original ResearchNatural language processingNatural language processing systemsLanguage modelExpansion of biomedical literatureZero-shot settingManually annotated corpusKnowledge graph developmentTask-specific modelsDomain-specific modelsZero-ShotEntity recognitionBillion parametersEnsemble learningLocation informationKnowledge basesBiomedical entitiesLanguage processingFree textGraph developmentBiomedical conceptsAutomated techniqueBiomedical literatureDetection methodPredictive performanceBiomedical knowledge
2023
Video Object Detection for Privacy-Preserving Patient Monitoring in Intensive Care
Emberger R, Boss J, Baumann D, Seric M, Huo S, Tuggener L, Keller E, Stadelmann T. Video Object Detection for Privacy-Preserving Patient Monitoring in Intensive Care. 2023, 00: 85-88. DOI: 10.1109/sds57534.2023.00019.Peer-Reviewed Original ResearchVideo object detectionClinical decision support systemObject detection methodShelf object detectorDecision support systemPatient monitoringImage color channelsPrivacy restrictionsVideo framesIT infrastructureObject detectionObject detectorObject classesHardware constraintsTemporal consistencySupport systemColor channelsBaseline modelImproved detection rateDetection methodReliable classificationProprietary datasetUnwanted artifactsInfrastructureInformation content
2021
Detecting model misconducts in decentralized healthcare federated learning
Kuo T, Pham A. Detecting model misconducts in decentralized healthcare federated learning. International Journal Of Medical Informatics 2021, 158: 104658. PMID: 34923447, PMCID: PMC10017272, DOI: 10.1016/j.ijmedinf.2021.104658.Peer-Reviewed Original ResearchFederated LearningFederated machine learningDetection methodDetection frameworkLearning iterationsMalicious intentLearning methodsMachine learningArtificial intelligenceParameter tuningComputational costCross-institutional collaborationLearningLearning processIterationPerformance detectorsDetectionIncorrect modelFrameworkAlgorithmDatasetDetect misconductIntelligencePlagiarismMethod
2017
Edge Detection Robust to Intensity Inhomogeneity: A 7T MRI Case Study
Cappabianco F, Lellis L, Miranda P, Ide J, Mujica-Parodi L. Edge Detection Robust to Intensity Inhomogeneity: A 7T MRI Case Study. Lecture Notes In Computer Science 2017, 10125: 459-466. DOI: 10.1007/978-3-319-52277-7_56.Peer-Reviewed Original ResearchEdge detection methodImage processing applicationsAutomatic edge detection methodDetection methodAccuracy of stateComputer visionNon-uniform intensityEdge detectionProcessing applicationsFundamental operationIntensity inhomogeneityHigh accuracyNumber of worksUltra-high field magnetic resonance imagingAccuracyGradient maximaCannyCase studyInhomogeneity correctionVisionRobustSmall numberBrain edgesMethodEdgeBenchmarks for measurement of duplicate detection methods in nucleotide databases
Chen Q, Zobel J, Verspoor K. Benchmarks for measurement of duplicate detection methods in nucleotide databases. Database 2017, 2023: baw164. PMID: 28334741, PMCID: PMC10755258, DOI: 10.1093/database/baw164.Peer-Reviewed Original ResearchDuplicate detection methodsNucleotide databaseUniProtKB/Swiss-ProtDetection methodMolecular biology researchData quality challengesPresence of duplicatesUniProt KnowledgebaseDuplicate detectionNucleotide sequenceCoding sequenceDatabase benchmarksDuplication of informationRecord linkage methodsExpert curationBiological researchBiological duplicatesBenchmarksNucleotideDuplicationTest efficiencyLinkage methods
2016
Colorimetric detection of proteins based on target-induced activation of aptazyme
Wu D, Gao T, Lei L, Yang D, Mao X, Li G. Colorimetric detection of proteins based on target-induced activation of aptazyme. Analytica Chimica Acta 2016, 942: 68-73. PMID: 27720123, DOI: 10.1016/j.aca.2016.09.010.Peer-Reviewed Original ResearchConceptsTarget proteinsDetection of proteinsCost-effective detectionAntibody-based assaysAptazymesTarget-induced activityGold nanoparticlesConformational changesDNA linkersProteinDetection of analytesProtein assayCross-linked gold nanoparticlesSignal amplificationEconomical synthesisAssayColorimetric detection of proteinDetection limitAssay methodSignal recognitionColorimetric detectionAnalytical performanceDetection methodGrowth factorDetection of vascular endothelial growth factorSupervised Learning for Detection of Duplicates in Genomic Sequence Databases
Chen Q, Zobel J, Zhang X, Verspoor K. Supervised Learning for Detection of Duplicates in Genomic Sequence Databases. PLOS ONE 2016, 11: e0159644. PMID: 27489953, PMCID: PMC4973881, DOI: 10.1371/journal.pone.0159644.Peer-Reviewed Original ResearchConceptsMulti-class modelSupervised learningMachine learningDe-duplicationGenome sequence databaseDetect duplicatesDuplicate detection methodsAutomatic systemAmount of dataDetection of duplicatesSequence databasesAblation studiesDetection contextMeta-dataDetection methodDatabase recordsExpert curationBiological databasesLearningCross-validationRecord featuresBinary modelSequence identityMachineDatabase
2015
Evaluation of a Machine Learning Duplicate Detection Method for Bioinformatics Databases
Chen Q, Zobel J, Verspoor K. Evaluation of a Machine Learning Duplicate Detection Method for Bioinformatics Databases. 2015, 4-12. DOI: 10.1145/2811163.2811175.Peer-Reviewed Original ResearchFinding duplicate recordsHandling large data setsDuplicate detection methodsLarge data setsMachine learning techniquesGeneral databasesImbalanced dataLearning techniquesImpact of duplicationDuplicate recordsDetection methodData setsDatabase recordsNucleotide databaseInconsistent recordsBioinformatics databasesBioinformaticsMachineBiological entitiesDatabaseDomain interpretationDuplicationTechniqueSpecialized techniquesGeneral method
2012
Automatic Detection of Subcellular Particles in Fluorescence Microscopy via Feature Clustering and Bayesian Analysis*
Liang L, Xu Y, Shen H, De Camilli P, Toomre D, Duncan J. Automatic Detection of Subcellular Particles in Fluorescence Microscopy via Feature Clustering and Bayesian Analysis*. 2012, 1: 161-166. DOI: 10.1109/mmbia.2012.6164750.Peer-Reviewed Original Research
2011
Extracting and integrating data from entire electronic health records for detecting colorectal cancer cases.
Xu H, Fu Z, Shah A, Chen Y, Peterson N, Chen Q, Mani S, Levy M, Dai Q, Denny J. Extracting and integrating data from entire electronic health records for detecting colorectal cancer cases. AMIA Annual Symposium Proceedings 2011, 2011: 1564-72. PMID: 22195222, PMCID: PMC3243156.Peer-Reviewed Original ResearchConceptsEntire electronic health recordElectronic health recordsNatural language processingHealth recordsStructured EHR dataMachine learningText dataNarrative text dataF-measureLanguage processingClinical narrativesEHR dataSuch tasksColorectal cancerDetection methodConcept identificationCohort of patientsColorectal cancer casesVanderbilt University HospitalCase detection methodsClinical notesCRC patientsCRC casesUniversity HospitalCancer cases
2010
Vascular Tree Reconstruction by Minimizing A Physiological Functional Cost
Jiang Y, Zhuang Z, Sinusas AJ, Papademetris X. Vascular Tree Reconstruction by Minimizing A Physiological Functional Cost. 2008 IEEE Computer Society Conference On Computer Vision And Pattern Recognition Workshops 2010, 178-185. PMID: 21755061, PMCID: PMC3132942, DOI: 10.1109/cvprw.2010.5543593.Peer-Reviewed Original ResearchA VTK-based, CUDA-optimized Non-Parametric Vessel Detection Method
Alpoge L, Joshi A, Scheinost D, Onofrey J, Qian X, Papademetris X. A VTK-based, CUDA-optimized Non-Parametric Vessel Detection Method. The VTK Journal 2010 DOI: 10.54294/z1w0uu.Chapters
2007
A study of abbreviations in clinical notes.
Xu H, Stetson P, Friedman C. A study of abbreviations in clinical notes. AMIA Annual Symposium Proceedings 2007, 2007: 821-5. PMID: 18693951, PMCID: PMC2655910.Peer-Reviewed Original ResearchConceptsUnified Medical Language SystemNatural language processing systemsLanguage processing systemNarrative clinical notesDetection methodClinical notesDifferent knowledge sourcesSense inventoryDomain expertsNLP systemsCorrect sensesDecision supportText corporaKnowledge sourcesError detectionProcessing systemBiomedical literatureStudy of abbreviationsLanguage systemPatient informationAmbiguity rateBetter detection methodsDatabaseAnnotationAbbreviations
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