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
Time-sensitive clinical concept embeddings learned from large electronic health records
Xiang Y, Xu J, Si Y, Li Z, Rasmy L, Zhou Y, Tiryaki F, Li F, Zhang Y, Wu Y, Jiang X, Zheng W, Zhi D, Tao C, Xu H. Time-sensitive clinical concept embeddings learned from large electronic health records. BMC Medical Informatics And Decision Making 2019, 19: 58. PMID: 30961579, PMCID: PMC6454598, DOI: 10.1186/s12911-019-0766-3.Peer-Reviewed Original ResearchConceptsConcept similarity measurePositive pointwise mutual informationConcept embeddingsSimilarity measurePredictive modeling tasksLarge electronic health recordTime-sensitive informationPointwise mutual informationImportant research areaDeep learningElectronic health recordsMedical domainLarge electronic health record databaseWord2vec embeddingsTemporal dependenciesLearning methodsFastText algorithmModeling tasksResultsOur experimentsExtrinsic evaluationIntrinsic evaluationMutual informationHealth recordsDistributional representationsEmbedding