Dr. Yan Huang is a Research Assistant Professor who studies clinical research informatics, ontology quality assurance, and artificial intelligence in healthcare. The overarching goal of his research is to design and develop systems for more efficient clinical data integration, processing management, and analysis. His work has practical applications in tools for large-scaled EHR, analysis of sleep data, multi-site epilepsy data integration and curation, and machine learning models for EEG signal classification.
Huang Y, Li X, Zhang GQ. ELII: A novel inverted index for fast temporal query, with application to a large Covid-19 EHR dataset. Journal of Biomedical Informatics. 2021 May 1;117:103744.
Huang Y, Li X, Dongarwar D, Wu H, Zhang GQ. Data Mining Pipeline for COVID-19 Vaccine Safety Analysis Using a Large Electronic Health Record. AMIA Summits on Translational Science Proceedings. 2023;2023:271.
Zhang GQ, Li X, Huang Y, Cui L. Temporal cohort logic. AMIA Annual Symposium Proceedings 2022 (Vol. 2022, p. 1237). American Medical Informatics Association.
Guo-Qiang Z, Yan H, Licong C. Can SNOMED CT changes be used as a surrogate standard for evaluating the performance of its auditing methods?. AMIA Annual Symposium Proceedings 2017 (Vol. 2017, p. 1903). American Medical Informatics Association.
Yao X, Li X, Ye Q, Huang Y, Cheng Q, Zhang GQ. A robust deep learning approach for automatic classification of seizures against non-seizures. Biomedical Signal Processing and Control. 2021 Feb 1;64:102215.