Xiaojun Ma, PhD
Data Scientist, IQVIA
Visiting Fellow, Graduate School of Medicine, The University of Tokyo
Xiaojun Ma received her PhD in Medical Science from The University of Tokyo, and MS and BS in Automation from Shanghai Jiao Tong University. She has nearly 10 years of experience in medical informatics, focusing on real-world data analysis including electronic health records, and claims. Her research interest is clinical information extraction by hybridising knowledge-based and data-driven approaches serving applications such as deep phenotyping. She has been working on medical ontology construction, clinical natural processing language, and application of machine learning in medicine especially dealing with the problem of lack of annotated data.
1. Ma, X, Shinohara E, Han H, Ishii M, Imai T, Ohe K. Extracting information on lifestyle issues from clinical narratives in EHR. JAMI 37(6): 313-321, 2017.
2. Ma, X, Imai T, Shinohara E, Sakurai R, Kozaki K, Ohe K. A Semi-automatic Framework to Identify Abnormal States in EHR Narratives. MEDINFO 2017: 910-914.
3. Ma, X., Shinohara, E., Sakurai, R., Kozaki, K., Imai, T., Ohe, K. High throughput identification of patients’ status from EHR. SIG-AIMED 2016.
4. Ma, X., Tomioka, K., Yamazaki, T., Yamashita, S., Murakami, K., Miyajima, T. Automatic case finding for cancer registry based on key medical documents. JHIM 2011; 23(2):185.
5. Ma, X., Hayashi, K., Miyajima, T. MRSA analysis based on pattern mining using DPC data. JCMI 2010; 30(Suppl):929-932.
