ScholarWorks@Gachon: Lee, Suehyun

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Lee, Suehyun (이수현)

College of IT Convergence (Department of Computer Engineering)

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Tel 031-750-5333
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adverse drug reaction:6||pharmacovigilance:5||COVID19:4||Machine learning:3||FAERS:2||Network analysis:2||Surgery:2||systematic review:2||WDBC(Wisconsin Diagnostic Breast Cancer):2||ARB:2||Big data:2||TabNet:2||healthcare:2||pharmacology:2||ACEI:2||hydroxymethylglutarylCoA reductase inhibitors:2||Electronic medical record:2||Artificial intelligence:2||.:2||Drug repositioning:2||realworld data:2||machine learning:2||Database:1||Databases:1||Deep Learning:1||Delayed treatment:1||Drug response:1||Drug side effects:1||Drug utilization review (DUR):1||DrugRelated Side Effects and Adverse Reactions:1||Drugs:1||EHR:1||East Asia:1||Efficiency:1||Elderly:1||Electronic health record:1||Endometriosis:1||Explainable ai:1||Feature extraction:1||Feature importance analysis:1||Generative Adversarial Networks:1||Generative adversarial networks:1||Genital tract infection:1||Health:1||Heart failure:1||Inflammation:1||Intention:1||KAERS:1||KaplanMeier estimation:1||Korean Adverse Event Reporting System:1||LDL:1||Laboratory measurement data:1||Lightgbm:1||Lung cancer:1||Mahalanobis distance:1||Medical data:1||Medical diagnostic imaging:1||MetaLAB:1||Metadata registry:1||Multiple drugs:1||Nnitrosodimethylamine:1||Neoadjuvant chemotherapy:1||Nurses:1||OMOPCDM:1||Organizational:1||PTA:1||PV:1||Partial dependence plot:1||Patient data:1||Patientcentered care:1||Patientgenerated health data (PGHD):1||Personalized medicine:1||Pharmacovigilance:1||Pipeline:1||Polypharmacy:1||Postmarketing surveillance:1||Prediction:1||Predictive models:1||Prescription data:1||Public response:1||RWD:1||RWE:1||Realworld data:1||Representation learning:1||SMART DATA:1||Safety:1||SelfSupervised learning:1||Semantic interoperability:1||Semantic relationship:1||Semantics:1||Social media analysis:1||Social network service:1||Spontaneous Reports:1||Survival analysis:1||Synthetic data:1||Tabular data:1||Task analysis:1||Time:1||Training:1||Transfer Learning:1||Transfer learning:1||Transfusion:1||Vaccine safety:1||Vaccines:1||adverse reaction:1||adverse reactions:1||angiotensin receptor antagonists:1||angiotensinconverting enzyme inhibitors:1||artificial intelligence:1||blockchain:1||cholesterol:1||chronic rhinosinusitis:1||common data model:1||data integration:1||datadriven approach:1||decentralized system:1||delta neutrophil index:1||detect:1||detection:1||diabetes:1||diabetes mellitus:1||differential privacy:1||disease prevention:1||distributed research network:1||drug reaction:1||drug safety:1||druginduced liver injury:1||dyslipidaemia:1||electronic health record:1||electronic health records:1||endoscopic sinus surgery:1||explainable artificial intelligence:1||ezetimibe:1||federated learning:1||gastric cancer:1||histamine2 blocker:1||homomorphic encryption privacy protection:1||irbesartan:1||kidney:1||losartan:1||machine learning method:1||medical big data:1||medical informatics:1||mobile health:1||multicenter study:1||nephrology:1||outlier remover:1||patientcentered system:1||personal health records:1||pharmaceutical:1||pharmaceutics:1||pharmacy:1||polyp:1||predictor:1||ranitidine:1||real world data:1||realworld evidence:1||reference standard:1||renal:1||semantic interoperatbility:1||statistical method:1||time series:1||time series AI:1||toxic:1||toxicity:1||uric acid:1||데이터 마이닝:1||딥러닝:1||보건:1||빅데이터:1||유방암:1||인공지능:1||정형 데이터:1||코로나19:1||ADR:1||ADRs:1||AI:1||Acute myocardial infarction:1||Adverse drug events (ADEs):1||Adverse drug reaction:1||Adverse drug reactions (ADR):1||Analysis methods:1||Beers criteria:1||Blockchain:1||Breast Cancer:1||Breast cancer:1||CDM:1||Cerebrovascular disease:1||Common data elements:1||Consumer sentiment:1||Cox regression model:1||Data mining:1||Data models:1||Data quality management system:1||Data science:1||

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1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114

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