Browsing "Biomedical Informatics" by Keyword : Machine Learning
Showing results 1 to 13 of 13
| Pub Year | | Title | Author(s) |
| 2021 | | A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data | 박래웅 |
| 2020 | | Analysis of Adverse Drug Reactions Identified in Nursing Notes Using Reinforcement Learning | 박래웅 |
| 2024 | | Applicable Machine Learning Model for Predicting Contrast-induced Nephropathy Based on Pre-catheterization Variables | 박래웅, 박인휘, 신규태, 이민정, 이윤지 |
| 2023 | | Association between impaired glucose metabolism and long-term prognosis at the time of diagnosis of depression: Impaired glucose metabolism as a promising biomarker proposed through a machine-learning approach | 노재성, 박래웅, 손상준, 조용혁 |
| 2009 | | Basic Concepts and Principles of Data Mining in Clinical Practice | 박래웅 |
| 2021 | | Effectiveness of transfer learning for deep learning-based electrocardiogram analysis | 윤덕용 |
| 2023 | | Feasibility Study of Federated Learning on the Distributed Research Network of OMOP Common Data Model | 박래웅 |
| 2024 | | Inter hospital external validation of interpretable machine learning based triage score for the emergency department using common data model | 박래웅 |
| 2018 | | Machine learning model combining features from algorithms with different analytical methodologies to detect laboratory-event-related adverse drug reaction signals | 박래웅, 윤덕용, 최영 |
| 2023 | | Machine learning-based prediction model for postoperative delirium in non-cardiac surgery | 김하연, 박래웅 |
| 2021 | | Machine-learning model to predict the cause of death using a stacking ensemble method for observational data | 박래웅, 정재연 |
| 2023 | | Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression: Prediction Model Development Study | 박래웅, 손상준 |
| 2023 | | Translation of Machine Learning-Based Prediction Algorithms to Personalised Empiric Antibiotic Selection: A Population-Based Cohort Study | 박래웅, 최영화 |
1
