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10.1002/jrsm.1044 [DOI] [PMC free article] [PubMed] 23.Chaimani A, Higgins JPT, Mavridis D et al (2013) Graphical tools for network meta-analysis in STATA

Adjustments were discussed clearly and I feel heard

That said, like any medical treatment, there are important considerations to keep in mind

Abbreviations ABLE: Asan Biomedical Research Environment database AMC: Asan Medical Center AI: Artificial intelligence AUROC: Area under the receiver operating characteristic curve BERT: Bidirectional encoder representation from transformers CABG: Coronary artery bypass grafting CKD: Chronic kidney disease CNN: Convolutional neural network CVD: Cardiovascular disease DB: Database DL: Deep learning DM: Diabetes mellitus EMR: Electronic medical record RF: Random forest GPT: Generative pre-trained transformer HF: Heart failure ICD: International Classification of Diseases of the World Health Organization IS: Ischemic stroke LOS: Length of stay LR: Logistic regression MACE: Major adverse cardiovascular events MI: Myocardial infarction MIMIC: Medical information mart for intensive care ML: Machine learning MLM: Masked language model NLP: Natural language processing OHE: One-hot encoding PAID: Patient identification PCI: Percutaneous coronary intervention PLMs: Pre-training language model RNN: Recurrent neural network RWE: Real-world evidence SVM: Support vector machine TG: Triglycerides T5: Text-to-Text Transfer Transformer t-SNE: t-distributed stochastic neighbor embedding W2V: Word2vec XGBoost: Extreme gradient boosting References Kim HS, Lee S, Kim JH

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