교수진 및 연구실 소개SAIHST에는 기초의학, 임상의학, 자연과학, 약학, 공학, 경영대학 등 Health Science와 관련된 다양한 분야를 전공한 교수진이 참여하고 있습니다.
미래의과학을 선도할 역량있는 교수의 참여를 기다립니다.
| 연구실소개 |
Smart Health Lab/차원철 교수 E-mail : smarthealthlab.smc@gmail.com Homepage : http://smarthealthlab.skku.edu/ 참여학과 : 디지털헬스학과 인쇄하기 |
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■ Research objective
Using innovative technology and data science, SHL dreams of improving and integrating healthcare ecosystem – people, environment, services, systems, and infrastructure. With user-centered design, we conduct an intervention study that includes analyzing data, developing predictive models, and applying our findings to real healthcare industries. SHL is a diverse community of different academic backgrounds, such as medicine, nursing, statistics, communication, design, and engineering. Our goal is to cultivate Digital Healthcare Scientists who can lead in various fields of healthcare industry. ■ Research interests 1)Integrating Health & IT We inspect the problems from various stakeholders’ perspectives and think about how to apply our IT skills and knowledge in the medical field. Due to patients’ safety and effectiveness, it is very hard to converge IT technology in the medical sector. At SHL, researchers and medical professionals act as intermediaries between healthcare and IT. We expect our works in IT innovations will bring a positive impact not only for patients, but also for many others in medical field. Integration of healthcare and IT comprehends the ER, ICU, wards, and everyday life outside hospital. We seek to create new value by solving problems in the field with experts from various fields. 2)Clinical Decision Support System We develop, apply, and evaluate our intelligent system that supports clinical decision both in patients’ and professionals’ level. We investigate interesting topics in clinical fields by interviewing medical staffs and patients, then develop predictive models using analytic skills on clinical data. Finally, we test our developed model for safety and scalability in multiple centers before applying it to actual field. Our current project includes detection of anomaly medication order, early detection of infectious disease, and clinical prognosis prediction of critical care patients. 3)Mobile Health SHL aims for the next-generation healthcare technology where everyone can be a owner of his or her health information. We want to find ways to collect and use meaningful data for personal and community healthcare. Mobile devices act as a hub that collects and analyzes patients’ medical and life-log information. SHL is currently conducting research to plan, develop, apply and evaluate EMR (mEMR) for medical staff and personal health records (PHR) for patients. 4)Common Data Model The medical is a nationwide system that various groups of people, such as patients, hospitals, medical staffs, insurance companies, and regulatory authorities are participating. Those groups who do not follow the standards are limited for collaborative works and other extra values. SHL develops OMOP CDM (Common Data Model) as standard for medical information and utilizes it for basis to develop predictive models. Furthermore, we are expanding the standard applications to the ER and ICU by using HL7FHIR, developing ECG result transmission modules. Although developing algorithms that comply with medical information standards requires a great deal of effort, it will make it possible to conduct extensive research with places where research is limited or at home and abroad. ■ Contact smarthealthlab.smc@gmail.com |