Intelligence and Control-based BioMedicine

지능 및 제어 기반 생명의학

관련기사 바로가기

본 연구팀은 데이터 기반 및 지식 기반의 모델을 활용하고 통합하여 의학과 생물학의 다양한 문제들을 정의하고 풀어내는 것을 목표로 한다. 이를 위해 여러 차원의 시계열을 포함한 다양한 데이터를 다루고, 통계와 제어공학, 최적화 이론 등을 비롯하여 머신러닝, 인공지능과 같은 다양한 방법론을 활용한다. 지식을 발견하는 과학부터 새로운 활용을 제안하는 공학까지, 임상의학과 생물학의 미충족 수요 뿐만 아니라 미발견 수요까지 새롭게 제안하고 해결하고자 한다. 의과학 및 임상의학 분야에서의, 예측과 추론에서부터 의사결정과 실행까지, 방법론 연구 및 실제 분야 적용의 영역에서 탐구하고 검증한다.
Our mission is to utilize and integrate data-based and knowledge-based models to define and solve various meaningful problems in medicine and biology. We deal with various types of data, including time series. To achieve this, we utilize diverse methodologies, including statistics, control, optimization theory, as well as machine learning and artificial intelligence. From the science of discovering knowledge to the engineering of proposing new applications, we aim to address not only the unmet demands in clinical medicine and biology but also to identify and solve undiscovered needs. We explore in the areas of methodology research and practical field applications, ranging from prediction and inference to decision-making and implementation in the biomedical sciences and clinical fields.

Major research field

Medical Data Science&Medical Informatics, Machine Learning&Artificial Intelligence in Biomedicine, Optimization&Control theory and its Medical App

Desired field of research

Medical Data Science&Medical Informatics, Machine Learning&Artificial Intelligence in Biomedicine, Optimization&Control theory and its Medical App

Research Keywords and Topics

· Integration of data-driven and knowledge-based models and methods in biomedical fields
· From biomedical science and engineering to clinical applications including prediction, prognosis, interventions, and decision making.
· Explainability and causality in prediction and control models for translational medicine
· (Clinical) domain knowledge distillation from and injection to data-driven and knowledge-based models
· Digital Healthcare and Literacy for Patients and Physicians

Research Publications

· Computer Methods and Programs in Biomedicine / A Practical Approach based on Learning-based Model Predictive Control with Minimal Prior Knowledge of Patients for Artificial Pancreas / M. H. Lim; et al. / 2023-06
· IEEE Journal of Biomedical and Health Informatics / Multi-Task Disentangled Autoencoder for Time-Series Data in Glucose Dynamics / M. H. Lim; et al. / 2022-09
· IEEE Access / A Blood Glucose Control Framework Based on Reinforcement Learning With Safety and Interpretability: In Silico Validation / M. H. Lim; et al. / 2021-07
· Stroke / Development of a Novel Prognostic Model to Predict 6-Month Swallowing Recovery After Ischemic Stroke / W. H. Lee, M. H. Lim; et al. / 2020-02


· Surgical robot system based on Headset using voice recognition Microphone
· Method for providing information for predicting dysphagia in patients with stroke
· Apparatus and method for symptom and disease management based on learning
· Online-based healthcare method and apparatus


  • LC. 보건의료
  • LC04. 치료·진단기기
  • LC0403. 지능형 판독시스템


  • 건강한 생명사회 지향
  • 021100. 생체신호처리기술


  • 녹색기술관련 과제 아님


  • BT 분야
  • 보건의료 관련응용
  • 020217. 의과학?의공학 기술