2025
Joint modeling of mixed outcomes using a rank-based sparse neural network
Xue J, Xu Y, Li J, Ma S, Fang K. Joint modeling of mixed outcomes using a rank-based sparse neural network. Journal Of Biomedical Informatics 2025, 169: 104870. PMID: 40623577, PMCID: PMC12306493, DOI: 10.1016/j.jbi.2025.104870.Peer-Reviewed Original ResearchSparse neural networksNeural networkCompetitive performanceImbalance issueLoss functionSparse layerLeverage informationPrediction accuracyTraditional methodsNetworkParametric frameworkPenalization methodFaces challengesJoint modelPrediction modelInformationSkin cutaneous melanomaHigh-throughput profilingHigh-dimensional covariatesDimensionalityGenomic researchFeaturesMethodSimulation studyBiomedical studiesA telescopic independent component analysis on functional magnetic resonance imaging dataset
Mirzaeian S, Faghiri A, Calhoun V, Iraji A. A telescopic independent component analysis on functional magnetic resonance imaging dataset. Network Neuroscience 2025, 9: 61-76. PMID: 40161992, PMCID: PMC11949590, DOI: 10.1162/netn_a_00421.Peer-Reviewed Original ResearchRight frontoparietal networkVisual networkIndependent component analysisBrain functionExtraction of informationFunctional magnetic resonance imaging datasetsImage datasetsFrontoparietal networkMagnetic resonance imaging datasetFMRI dataGroup differencesLeverage informationSmall networksDMNNetworkComponent analysisIncomplete viewAbstract Brain functionFunctional source
2024
Refining Biologically Inconsistent Segmentation Masks with Masked Autoencoders
Sauer A, Tian Y, Bewersdorf J, Rittscher J. Refining Biologically Inconsistent Segmentation Masks with Masked Autoencoders. 2008 IEEE Computer Society Conference On Computer Vision And Pattern Recognition Workshops 2024, 00: 6904-6912. PMID: 39669420, PMCID: PMC7617224, DOI: 10.1109/cvprw63382.2024.00684.Peer-Reviewed Original Research
2022
Improving Pharmacovigilance Signal Detection from Clinical Notes with Locality Sensitive Neural Concept Embeddings.
Mower J, Bernstam E, Xu H, Myneni S, Subramanian D, Cohen T. Improving Pharmacovigilance Signal Detection from Clinical Notes with Locality Sensitive Neural Concept Embeddings. AMIA Joint Summits On Translational Science Proceedings 2022, 2022: 349-358. PMID: 35854716, PMCID: PMC9285153.Peer-Reviewed Original ResearchNatural language processingClinical notesRetrieval tasksConcept embeddingsNeural embeddingsLeverage informationLanguage processingEmbedding methodPharmacovigilance signal detectionADR signalsInherent complexityEmbeddingSignal detectionSignal recoveryAdverse drug reactionsStatistical measuresInformationDetection
2019
Testing predictability of disease outbreaks with a simple model of pathogen biogeography
Dallas T, Carlson C, Poisot T. Testing predictability of disease outbreaks with a simple model of pathogen biogeography. Royal Society Open Science 2019, 6: 190883. PMID: 31827836, PMCID: PMC6894608, DOI: 10.1098/rsos.190883.Peer-Reviewed Original ResearchPathogen outbreaksCo-occurring pathogensPredicting disease emergencePathogen geographic distributionOutbreak eventsPathogen communitiesHuman infectious diseasesPathogen typesPathogensGeographical distributionBiogeographyTest predictionsDisease emergenceGlobal disease surveillancePairwise dissimilaritiesLeverage informationDisease outbreaksInfluenza pandemicGlobal emergencyPublic health professionalsRe-emergenceGlobal view
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply