Biography:

Teng Fei received her B.S. degree and M.S. degree from the Southwest Jiaotong University, China in 2006 and 2008, respectively. She received her Ph.D degree at Ecole Centrale Paris in France in 2011. She is an associate professor at School of Computing and Artificial Intelligence, Southwest Jiaotong University, China. Her research interests include cloud computing, industrial data mining. She has published one monograph and 50+ research papers in A rank international journals and conferences, and received 10+ Chinese invention patents in the field of medical knowledge graph and clinical text mining. Dr. Teng serves as the reviewer of IEEE Journal of Biomedical and Health Informatics, Information Sciences, IEEE transaction on Computers. She has chaired GreenCom, Chinavis and PAKDD, and served on the technical program committee board for 20+ international conferences

Speech title: Explainable Prediction of ICD coding With Knowledge Graphs

Abstract:

International Classification of Diseases (ICD) is an authoritative healthcare classification system of different diseases. It is widely used for disease and health records, assisted medical reimbursement decisions, and collecting morbidity and mortality statistics. This talk will present how deap neural netwoks been applied in ICD coding to deal with challenges, such as complex feature extraction, biased label distribution, integrating external knowledge and model interpretability, and meanwhile introduce some prospects to promote ICD coding research in smart healthcare.