| 2021-11 | Artificial intelligence model comparison for risk factor analysis of patent ductus arteriosus in nationwide very low birth weight infants cohort | 이주현 |
| 2021-06 | Automatic Classification of the Korean Triage Acuity Scale in Simulated Emergency Rooms Using Speech Recognition and Natural Language Processing: a Proof of Concept Study | 이주현 |
| 2019-06 | Beyond Max-weight Scheduling: A Reinforcement Learning-based Approach | 이주현 |
| 2017-01 | CarrierMix: How Much Can User-side Carrier Mixing Help? | 이주현 |
| 2017-03 | CAS: Context-Aware Background Application Scheduling in Interactive Mobile Systems | 이주현 |
| 2023-12 | Deep learning-based natural language processing for detecting medical symptoms and histories in emergency patient triage | 이주현 |
| 2019-12 | Delay-Optimal and Energy-Efficient Communications with Markovian Arrivals | 이주현 |
| 2017-04 | Delay-Optimal Buffer-Aware Scheduling With Adaptive Transmission | 이주현 |
| 2018-06 | Finding minimum node separators: A Markov chain Monte Carlo method | 이주현 |
| 2019-09 | An Inter-data Encoding Technique that Exploits Synchronized Data for Network Applications | 이주현 |
| 2021-07 | Joint Queue-Aware and Channel-Aware Scheduling for Non-Orthogonal Multiple Access | 이주현 |
| 2021-01 | Learning to Schedule Network Resources Throughput and Delay Optimally Using Q+-Learning | 이주현 |
| 2021-12 | LSTM-based Throughput Prediction for LTE Networks | 이주현 |
| 2021-08 | Machine Learning and Deep Learning for Throughput Prediction | 이주현 |
| 2022-02 | Machine learning-based diagnosis and risk factor analysis of cardiocerebrovascular disease based on KNHANES | 이주현 |
| 2022-02 | Machine learning‑based diagnosis and risk factor analysis of cardiocerebrovascular disease based on KNHANES | 이주현 |
| 2023-08 | Multi-agent deep reinforcement learning for cross-layer scheduling in mobile ad-hoc networks | 이주현 |
| 2018-07 | A Near-Optimal Control Policy in Cloud Systems with Renewable Sources and Time-dependent Energy Price | 이주현 |
| 2023-02 | NOMA-based Random Access: Multi-Agent Reinforcement Learning Method | 이주현 |
| 2021-05 | Prediction of Head Movement in 360-Degree Videos Using Attention Model | 이주현 |
| 2020-02 | Prediction of Network Throughput using ARIMA | 이주현 |
| 2018-04 | Pricing for Past Channel State Information in Multi-Channel Cognitive Radio Networks | 이주현 |
| 2021-06 | Q-greedyUCB: a New Exploration Policy to Learn Resource-Efficient Scheduling | 이주현 |
| 2019-11 | Q-Learning을 활용한 개인의 의료비 최소화 연구 | 이주현 |
| 2019-10 | A Reinforcement Learning Based Low-Delay Scheduling With Adaptive Transmission | 이주현 |
| 2021-04 | Reinforcement Learning for Random Access in Multi-cell Networks | 이주현 |
| 2016-12 | Resource-Efficient Mobile Multimedia Streaming With Adaptive Network Selection | 이주현 |
| 2021-02 | 다중 안테나 기술에서의 딥러닝 기반 직교 진폭 변조 디코더 | 이주현 |
| 2020-08 | 다중슬롯머신과 최신 통신 시스템 응용 | 이주현 |
| 2020-08 | 딥러닝 기반 나이 예측과 자연어처리를 활용한 의류추천 시스템 | 이주현 |
