Yan Lee

Yan Long Lee is a dedicated Analyst at SingHealth, where he plays a pivotal role in advancing clinical research and data analytics initiatives. His current responsibilities involve designing and maintaining sophisticated data pipelines and tools that facilitate the secure de-identification of DICOM image files, ensuring patient privacy while supporting medical imaging research. Leveraging his expertise in Python programming, Yan has developed robust Docker images that streamline the de-identification process, significantly enhancing operational efficiency and compliance with data protection regulations.

In addition to his work in image de-identification, Yan manages the transformation of complex clinical research data into the OMOP Common Data Model (CDM), enabling seamless data sharing and interoperability across research projects. His proficiency in data transformation, coupled with his experience in system administration for OLAP systems like ODySSEy, ensures that data warehouses are optimized for analytical queries and reporting. Yan’s familiarity with statistical data analysis and machine learning tools such as Scikit-learn and Keras allows him to extract actionable insights from large datasets, supporting evidence-based decision-making.

Beyond his core responsibilities, Yan’s technical versatility extends to areas like web scraping, Boto3 for AWS automation, and basic network configuration, which contribute to his holistic approach to data management and system support. His knowledge of programming languages including JavaScript, C, and Java, along with skills in Windows Server and Zebra Programming Language, further bolster his ability to troubleshoot and develop innovative solutions. Yan Long Lee’s blend of technical expertise, research support, and project management makes him a valuable asset in Singapore’s healthcare data ecosystem, driving forward initiatives that improve patient outcomes and operational efficiencies.