معرفی
Na Hong is an Instructor of Biomedical Informatics and Data Science at Yale School of Medicine. She holds a PhD in Information Science from the Chinese Academy of Sciences (2010) and completed postdoctoral training in Medical Informatics at Mayo Clinic (2018). Her research focuses on clinical data standards (OHDSI, FHIR, i2b2), data normalization/harmonization, and applications in electronic health records (EHRs). She has contributed to grants and co-authored over 80 peer-reviewed publications.
- Education:
- PhD in Information Science, Chinese Academy of Sciences, 2010
- Postdoctoral Training in Medical Informatics, Mayo Clinic, 2018
Research Interests: Her work emphasizes interoperability of clinical data through standards like FHIR and OHDSI, with applications in predictive modeling for diseases such as lung cancer and sepsis. She develops tools for clinical decision support systems and integrates unstructured EHR data using NLP. Recent projects include risk prediction models for venous thromboembolism and sepsis outcomes, leveraging machine learning.
Publications: Her 15 most recent articles span machine learning in ICU decision-making, FHIR-based data normalization, and pharmacovigilance platforms. These reflect her focus on bridging data standards with clinical practice.
- Grants & Contributions:
- Co-investigator/key researcher in multiple grants
- Developed frameworks for EHR phenotyping and cohort retrieval systems
Labs/Teams: Active in Biomedical Informatics & Data Science initiatives at Yale, contributing to projects like the NIH-funded Mental Health Research using AI.
