Research Areas
Artificial Intelligence in Healthcare
Medical Image Analysis
Medical images account for the majority of medical data, acquired from various imaging equipment such as x-ray, CT, MRI, ultrasonography, endoscopy, etc., as well as all types of images related to patients in medical institute. We analyze medical images from hospitals by applying image processing and deep learning technologies.
Biosignal Analysis
Biosignals indicate health status in real-time. In addition to vital signs from the ORs and the wards, there are signals measured for examination and wearable devices. We analyze biosignals from hospitals and during daily life by applying signal processing and deep learning technologies.
Omics Data Analysis
The field of Omics is divided into Genomics & Epigenomics, Transcriptomics, Metabolomics, and Proteomics according to biological aspects. We analyze various biological data from the DNA level for understanding life phenomena to the molecule level for drug discovery by applying deep learning technologies in bioinformatics.
Life-log Data Analysis
Lifelog data is not measured by medical institutions, but includes exercise and healthcare data measured with a mobile phone or IoT sensor during daily life. We analyze lifelog data considering the characteristics by applying machine learning, and deep learning technologies.
EHR Analysis
Electronic Health Records(EHR) contain key patient information and can be shared in different healthcare environments. We support clinicians who want to utilize EHR-Common Data Model(CDM), and perform multimodal data research that connects to unstructured data and EHR-CDM.
Extended Reality in Healthcare
Augmented Reality assisted Surgery
The Augmented Reality(AR) technology is utilized to assist the surgery by registration of patient's anatomical structures. We research the segmentation method for 3D anatomical structures from patient images before surgery, and registration method for overlaying on the target position during surgery.
Virtual Medical Simulation & Training
Virtual Reality(VR) technology is utilized to build a virtual environment to overcome the physical limitations of patients and clinicians. It can be utilized as digital therapeutics for patients and training to improve clinical performance. We develop content in various environments and research ML-Agents based simulation to satisfy clinical unmet needs.