Basic Enhancement Strategies When Using Bayesian Optimization for Hyperparameter Tuning of Deep Neural Networks H Cho, Y Kim, E Lee, D Choi, Y Lee, W Rhee IEEE Access 8, 52588-52608, 2020 | 153 | 2020 |
Churn prediction of mobile and online casual games using play log data S Kim, D Choi, E Lee, W Rhee PloS one 12 (7), e0180735, 2017 | 84 | 2017 |
The ENERTALK dataset, 15 Hz electricity consumption data from 22 houses in Korea C Shin, E Lee, J Han, J Yim, W Rhee, H Lee Scientific data 6 (1), 193, 2019 | 74 | 2019 |
Individualized Short-Term Electric Load Forecasting With Deep Neural Network Based Transfer Learning and Meta Learning E Lee, W Rhee IEEE Access 9, 15413-15425, 2021 | 38 | 2021 |
Defining virtual control group to improve customer baseline load calculation of residential demand response E Lee, K Lee, H Lee, E Kim, W Rhee Applied Energy 250, 946-958, 2019 | 29 | 2019 |
Learning ECG Representations for Multi-Label Classification of Cardiac Abnormalities J Suh, J Kim, E Lee, J Kim, D Hwang, J Park, J Lee, J Park, SY Moon, ... 2021 Computing in Cardiology (CinC) 48, 1-4, 2021 | 12 | 2021 |
Aid-purifier: A light auxiliary network for boosting adversarial defense D Hwang, E Lee, W Rhee Neurocomputing 541, 126251, 2023 | 8 | 2023 |
Improving the Energy Saving Process with High-Resolution Data: A Case Study in a University Building J Han, E Lee, H Cho, Y Yoon, H Lee, W Rhee Sensors 18 (5), 1606, 2018 | 7 | 2018 |
Assuring explainability on demand response targeting via credit scoring K Lee, H Lee, H Lee, Y Yoon, E Lee, W Rhee Energy 161, 670-679, 2018 | 6 | 2018 |
Incidence, risk factors, and outcomes of atrial functional mitral regurgitation in patients with atrial fibrillation or sinus rhythm JA Naser, HI Michelena, G Lin, CG Scott, E Lee, AM Kennedy, ... European Heart Journal-Cardiovascular Imaging 24 (11), 1450-1457, 2023 | 5 | 2023 |
Prevalence and incidence of diastolic dysfunction in atrial fibrillation: clinical implications JA Naser, E Lee, CG Scott, AM Kennedy, PA Pellikka, G Lin, SV Pislaru, ... European Heart Journal 44 (48), 5049-5060, 2023 | 4 | 2023 |
Artificial intelligence-enabled ECG for left ventricular diastolic function and filling pressure E Lee, S Ito, WR Miranda, F Lopez-Jimenez, GC Kane, SJ Asirvatham, ... npj Digital Medicine 7 (1), 4, 2024 | 3 | 2024 |
Correlation between artificial intelligence-enabled electrocardiogram and echocardiographic features in aortic stenosis S Ito, M Cohen-Shelly, ZI Attia, E Lee, PA Friedman, VT Nkomo, ... European Heart Journal-Digital Health 4 (3), 196-206, 2023 | 3 | 2023 |
DEEP-BO for Hyperparameter Optimization of Deep Networks H Cho, Y Kim, E Lee, D Choi, Y Lee, W Rhee arXiv preprint arXiv:1905.09680, 2019 | 3 | 2019 |
Machine learning prediction for the recurrence after electrical cardioversion of patients with persistent atrial fibrillation S Kwon, E Lee, H Ju, HJ Ahn, SR Lee, EK Choi, J Suh, S Oh, W Rhee Korean Circulation Journal 53 (10), 677, 2023 | 2 | 2023 |
소규모 전력 소비자 대상 수요자원 거래시장의 필요성 및 시범운영 결과 분석 이은정, 이경은, 이혜수, 이효섭, 김은철, 이원종 한국통신학회논문지 42 (4), 915-922, 2017 | 2 | 2017 |
ARTIFICIAL INTELLIGENCE-ENHANCED ELECTROCARDIOGRAPHY IDENTIFIES PATIENTS WITH NORMAL EJECTION FRACTION AT RISK OF WORSE OUTCOMES JA Naser, E Lee, F Lopez-Jimenez, P Noseworthy, O Latif, PA Friedman, ... Journal of the American College of Cardiology 83 (13_Supplement), 2572-2572, 2024 | | 2024 |
Artificial intelligence-based classification of echocardiographic views JA Naser, E Lee, SV Pislaru, G Tsaban, JG Malins, JI Jackson, ... European Heart Journal-Digital Health, ztae015, 2024 | | 2024 |
Enhancing Contrastive Learning with Efficient Combinatorial Positive Pairing J Kim, D Hwang, E Lee, J Suh, J Kim, W Rhee arXiv preprint arXiv:2401.05730, 2024 | | 2024 |
A View-Invariant Deep Learning Model for Estimating Ejection Fraction From Any Valid Echocardiogram Videoclip, Including Point-of-Care Ultrasound (POCUS) DM Anisuzzaman, JG Malins, JI Jackson, E Lee, J Naser, B Rostami, ... Circulation 148 (Suppl_1), A16836-A16836, 2023 | | 2023 |