A scoping review of fair machine learning techniques when using real-world data
Huang Y, Guo J, Chen W, Lin H, Tang H, Wang F, Xu H, Bian J. A scoping review of fair machine learning techniques when using real-world data. Journal Of Biomedical Informatics 2024, 151: 104622. PMID: 38452862, PMCID: PMC11146346, DOI: 10.1016/j.jbi.2024.104622.Peer-Reviewed Original ResearchConceptsReal-world dataHealth care applicationsHealth care domainMachine learningArtificial intelligenceCare applicationsMulti-modal dataIntegration of artificial intelligenceMachine learning techniquesPre-processing techniquesCare domainBias mitigation approachesPublic datasetsAI/ML modelsModel fairnessLearning techniquesOptimal fairnessHealth care dataAI toolsHealth careAlgorithmic biasML modelsAI/MLFairnessBias issuesArtificial intelligence-powered pharmacovigilance: A review of machine and deep learning in clinical text-based adverse drug event detection for benchmark datasets
Li Y, Tao W, Li Z, Sun Z, Li F, Fenton S, Xu H, Tao C. Artificial intelligence-powered pharmacovigilance: A review of machine and deep learning in clinical text-based adverse drug event detection for benchmark datasets. Journal Of Biomedical Informatics 2024, 152: 104621. PMID: 38447600, DOI: 10.1016/j.jbi.2024.104621.Peer-Reviewed Original ResearchNamed-entity recognitionEnd-to-end tasksEnd-to-endMachine learningBenchmark datasetsAdverse drug event extractionNamed-entity recognition taskLearning modelsAdverse drug event detectionBidirectional Encoder RepresentationsDeep learning techniquesDeep learning methodsDeep learning modelsEffectiveness of machine learningDeep learning methodologyMachine learning modelsSocial media dataEncoder RepresentationsEvent detectionDeep learningLearning techniquesMultilayer perceptronLearning methodsMedia dataRC task