2023
MonoNet: enhancing interpretability in neural networks via monotonic features
Nguyen A, Moreno D, Le-Bel N, Martínez M. MonoNet: enhancing interpretability in neural networks via monotonic features. Bioinformatics Advances 2023, 3: vbad016. PMID: 37143924, PMCID: PMC10152389, DOI: 10.1093/bioadv/vbad016.Peer-Reviewed Original ResearchNeural networkMonotonicity constraintsHigh-stakes scenariosInformation-theoretic analysisMachine learning modelsMedical informaticsNeural modelLearning capabilityLearning modelsBioinformatics Advances</i>Monotonous featuresComputational biologyEnhance interpretationModeling capabilitiesDatasetInterpretable modelsLearning processSample dataNetworkPower modelLearningSupplementary dataConstraintsPerformanceInformatics
2020
Integrative statistical methods for exposure mixtures and health
Reich BJ, Guan Y, Fourches D, Warren JL, Sarnat SE, Chang HH. Integrative statistical methods for exposure mixtures and health. The Annals Of Applied Statistics 2020, 14: 1945-1963. PMID: 35284031, PMCID: PMC8914338, DOI: 10.1214/20-aoas1364.Peer-Reviewed Original ResearchIntegrative statistical methodsStatistical methodsAuxiliary informationFlexible Bayesian modelInnovative statistical toolsPrior distributionVolatile organic compoundsStatistical toolsBayesian modelOrganic compoundsInterpretable modelsSpectrum of analysisRole of mixturesEmergency room visitsChemical mixturesDiverse chemicalsMixture constituentsNew methodRoom visitsMixtureEnvironmental epidemiologyMeasured exposureChemicalsAdverse health outcomesToxicological data
2019
From Big Data to Precision Medicine
Hulsen T, Jamuar SS, Moody AR, Karnes JH, Varga O, Hedensted S, Spreafico R, Hafler DA, McKinney EF. From Big Data to Precision Medicine. Frontiers In Medicine 2019, 6: 34. PMID: 30881956, PMCID: PMC6405506, DOI: 10.3389/fmed.2019.00034.Peer-Reviewed Original ResearchBig dataLarge datasetsLarge volume informationElectronic health record miningLarge data volumesData analyticsVelocity of informationData contentRecords miningData scienceData volumeMedical researchersInterpretable modelsHypothesis-driven methodsData-driven hypothesesCollaborative networksAnalyticsAnalytic methodologyVolume informationDatasetImportant challengeNew technologiesHypothesis-generating researchConventional approachesData collection
2016
OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems
Ogbunugafor C, Robinson S. OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems. PLOS ONE 2016, 11: e0156844. PMID: 27270918, PMCID: PMC4896432, DOI: 10.1371/journal.pone.0156844.Peer-Reviewed Original ResearchConceptsWeighted directed graphRelational databaseModels of dynamical systemsSoftware implementationTransformation rulesDynamic models of biological systemsNovel schemaModel schemaModels of biological systemsFlow diagramModel building processDirected graphSystem of ordinary differential equationsSchemaInterpretable modelsEquivalent representationOrdinary differential equationsFormalized versionConsumer-resource modelsDynamical systemsBuilding processChief motivationTarget speciesComplex modelsImplementation
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