Psychiatric stressor recognition from clinical notes to reveal association with suicide
Zhang Y, Zhang O, Li R, Flores A, Selek S, Zhang X, Xu H. Psychiatric stressor recognition from clinical notes to reveal association with suicide. Health Informatics Journal 2018, 25: 1846-1862. PMID: 30328378, DOI: 10.1177/1460458218796598.Peer-Reviewed Original ResearchConceptsElectronic health recordsSuicidal behaviorHealth recordsSuicide ideation/attemptsTremendous economic burdenPsychiatric stressorsSuicide risk factorsRisk factorsEconomic burdenPsychiatric stressClinical notesLarge-scale studiesPsychiatric notesSuicideAssociationSignificant stressorsStressorsPrior studiesPercentPrevious studiesStudyExtracting psychiatric stressors for suicide from social media using deep learning
Du J, Zhang Y, Luo J, Jia Y, Wei Q, Tao C, Xu H. Extracting psychiatric stressors for suicide from social media using deep learning. BMC Medical Informatics And Decision Making 2018, 18: 43. PMID: 30066665, PMCID: PMC6069295, DOI: 10.1186/s12911-018-0632-8.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsDeep LearningHumansNeural Networks, ComputerSocial MediaStress, PsychologicalSuicide PreventionConceptsConvolutional neural networkRecurrent neural networkDeep learningConditional Random FieldsSupport vector machineSuicide-related tweetsClinical textNeural networkPsychiatric stressorsExtra TreesBinary classifierTransfer learning strategiesEntity recognition taskSocial mediaExact matchTraditional machineAnnotation costLearning strategiesRecognition problemSharing flowInexact matchVector machineTwitter dataRecognition taskTwitter