Minseok Song
포항공과대학교 경영학과 · 경영학
송민석 교수의 연구실은 헬스케어 정보 시스템, 블록체인 기반 의료정보 교환, 그리고 지능형 의사결정 지원 시스템을 중심으로 연구를 전개하고 있습니다. 특히 환자 입원일수 최적화, 의료정보의 보안적 공유, 수소 연료 전지 인프라 설계 등 실생활 문제 해결을 목표로 한 기술 기반의 디자인 과학적 접근을 강조합니다. 최근에는 딥러닝 기반 스포츠 분석 기술을 활용한 선수 플레이 스타일 분석 등 데이터 기반 지능형 시스템 개발에도 진출하여 다학제적 연구를 확장하고 있습니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
Accurate understanding of the factors associating with the LOS and progressive improvements in processing and monitoring may allow more efficient management of the LOS of inpatients.
Health information exchange (HIE) refers to the integrated management and secure sharing of health information among healthcare entities. HIE improves healthcare quality and streamline healthcare administrative work. These advantages have propelled health-care stakeholders to implement HIE. However, challenged by issues such as security, privacy, and costs, HIE is not widespread. Recent studies have suggested blockchain-based HIE for solving security and privacy issues. Unfortunately, existing b
This study presents a novel web-based decision support system (DSS) that optimizes the locations of hydrogen refueling stations (HRSs) and hydrogen supply chains (HSCs). The system is developed with a design science approach that identifies key design requirements and features through interviews and literature reviews. Based on the findings, a system architecture and data model were designed, incorporating scenario management, optimization model, visualization, and data management components. Th
The aim of this research was to analyze the player’s pass style with enhanced accuracy using the deep learning technique. We proposed Pass2vec, a passing style descriptor that can characterize each player’s passing style by combining detailed information on passes. Pass data was extracted from the ball event data from five European football leagues in the 2017–2018 season, which was divided into training and test set. The information on location, length, and direction of passes was combined usin
