Jinying Chen, PhD
Assistant Professor, Medicine

Biography
Jinying Chen, PhD, is an assistant professor of Department of Medicine/Section of Preventive Medicine and Epidemiology and a faculty member of Data Science Core at Boston University Chobanian & Avedisian School of Medicine. She also serves as the chair of the Action Group of Technology in Implementation Science in the Consortium for Cancer Implementation Science (CCIS).
Dr. Chen has a PhD in Computer and Information Science from the University of Pennsylvania and is specialized in natural language processing (NLP) and machine learning. She received postdoctoral training in Health Sciences, including biostatistics, health informatics, and implementation science, from the University of Massachusetts Chan Medical School. Dr. Chen’s research focuses on method innovations (NLP, machine learning/deep learning, big data analytics, and biostatistics) to support public health and health services research. Her research areas include:
NLP and Machine Learning for Health Services Research. Dr. Chen developed and user tested NoteAid, the first NLP system that automatically links medical terms in electronic health record (EHR) notes to lay-language definitions to help patients comprehend their notes. She applied a variety of machine learning techniques, including tree-based and graph-based ensemble learning and transfer learning, to support the development of NoteAid. Working with physician scientists, she developed NLP systems and methods to extract information (e.g., COVID-19 symptoms, pain symptoms, hypoglycemia events, cognitive test results) from EHR free text to support epidemiology studies and the creation of a national cohort of patients with Alzheimer’s disease. She is the 2023 recipient of the LTC Data Cooperative’s Real-World Data Scholarship and is leading an initiative to validate billions of medication records in the LTC dataset using NLP and large language models (LLMs).
Risk Prediction, Digital Biomarkers, and Deep Phenotyping for Brain Health. Since joining BU, Dr. Chen has been working with other BU faculty members to develop and apply advanced data science methods to brain health research. She is the recipient of the 2023 pilot award from the Framingham Heart Study Brain Aging Program (FHS-BAP) to lead the efforts in developing a new construct-based approach to improve the interpretability and generalizability of machine learning-based risk prediction for Alzheimer’s disease (AD). Other work includes developing new methods that leverage LLMs to support biomedical data harmonization, investiging social and societal factors influencing AD progression and care, applying deep learning techniques for AD phenotyping and progression prediction, and developing speech markers for AD risk.
Innovation in Implementation Science Methods. As a K12 scholar in implementation science, Dr. Chen developed implementation strategies to support pain assessment in cardiovascular patients post discharge and used NLP to enhance patient recruitment and statistical analysis. As the recipient of a pilot award from the NCI-funded iDAPT Implementation Science Center for Cancer Control, she developed EHR-based metrics and machine learning methods (e.g., unsupervised statistical latent-variable learning models) to identify clinical activity patterns from EHR logs and successfully applied this approach to monitor the impact of tobacco cessation tools implemented in cancer clinics. Her approach integrated methods from biostatistics, machine learning, and NLP.
Digital Health Interventions and Tools. Dr. Chen collaborated with researchers from University of Massachusetts Chan Medical School, Wake Forest School of Medicine, Boston University, and Implementation Science Centers for Cancer Control (ISC3) to study the effects of digital health interventions and tools. She has led or contributed to projects that (1) assessed longitudinal behavior change in people who smoke following digital health interventions, using statistical methods such as generalized estimating equation models, time-to-event analysis, and multiple imputation to handle missing data; (2) assessed users’ adoption and engagement with digital health interventions in a variety of settings, including cognitive assessment testing, smoking cessation, transitional care, tobacco screening, and cancer screening.
Education
- University of Pennsylvania, PhD
- University of Pennsylvania, MS
- Tsinghua University, ME/MEng
- Tsinghua University, BS
Classes Taught
- FC721
Publications
- Published on 7/10/2024
Lu J, Chen J. The 22nd International Conference on Artificial Intelligence in Medicine (AIME 2024). Developing and Validating Large Language Model-Based Approaches for Detecting Misspelled Drug Names. 2024.
- Published on 4/30/2024
Owens-Jasey C, Chen J, Xu R, Angier H, Huebschmann AG, Ito Fukunaga M, Chaiyachati KH, Rendle KA, Robien K, DiMartino L, Amante DJ, Faro JM, Kepper MM, Ramsey AT, Bressman E, Gold R. Implementation of Health IT for Cancer Screening in US Primary Care: Scoping Review. JMIR Cancer. 2024 Apr 30; 10:e49002. PMID: 38687595.
Read at: PubMed - Published on 4/22/2024
Huguet N, Chen J, Parikh RB, Marino M, Flocke SA, Likumahuwa-Ackman S, Bekelman J, DeVoe JE. Applying Machine Learning Techniques to Implementation Science. Online J Public Health Inform. 2024 Apr 22; 16:e50201. PMID: 38648094.
Read at: PubMed - Published on 3/20/2024
Li Z, Prabhu SP, Popp ZT, Ang TFA, Au R, Chen J. 2024 AMIA Informatics Summit. Using Natural Language Processing for Data Harmonization: Comparing Large Language Models and Fuzzy Matching Approaches. 2024.
- Published on 3/6/2024
Jain SS, Ang TFA, Sunderaraman P, Au R, Chen J. The AD/PD™ 2024 Alzheimer's & Parkinson's Diseases Conference. Caregiver Gender Differences with respect to Costs and Caregiver Burden Associated with Community-Dwelling Patients with Alzheimer's Disease. 2024.
- Published on 3/6/2024
Zachary T. Popp, Ang TFA, Au R, Chen J. The AD/PD™ 2024 Alzheimer's & Parkinson's Diseases Conference. Impacts of Education on Rates of Cognitive Decline in Alzheimer's Disease Patients: Results From a Multinational European Observational Study. 2024.
- Published on 1/1/2024
Morin P, Aguilar BJ, Li X, Chen J, Berlowitz D, Zhang R, Tahami Monfared AA, Zhang Q, Xia W. Alzheimer's Disease Stage Transitions Among United States Veterans. J Alzheimers Dis. 2024; 97(2):687-695. PMID: 38143359.
Read at: PubMed - Published on 8/1/2023
Jiaoyun Yang, Richu Jiang, Huitong Ding, Rhoda Au, Jinying Chen, Clara Li, Ning An. HCI International 2023–Late Breaking Papers: Human Aspects of IT for the Aged Population 2023, Proceedings (full paper). Designing and Evaluating MahjongBrain: A Digital Cognitive Assessment Tool through Gamification. 2023.
- Published on 7/16/2023
Jinying Chen, Xuyang Li, Byron J. Aguilar, Ekaterina Shishova, Peter Morin, Dan Berlowitz, Donald R. Miller, Maureen K O’Connor, Andrew Nguyen, Raymond Zhang, Amir Abbas Tahami Monfared, Quanwu Zhang, Weiming Xia. AAIC23: 2023 Alzheimer’s Association International Conference, Amsterdam, Netherlands, July 16-20, 2023. Development and validation of a natural language processing system that extracts cognitive test results from clinical notes. 2023.
- Published on 3/31/2023
Jinying Chen, Byron J. Aguilar, Xuyang Li, Peter Morin, Dan Berlowitz, Donald R. Miller, Jingmei Yang, Boran Hao, Raymond Zhang, Amir Abbas Tahami Monfared, Quanwu Zhang, Ioannis Ch. Paschalidis, Weiming Xia. AD/PDTM23: 17th International Conference on Alzheimer’s & Parkinson’s Diseases. Gothenburg, Sweden, March 28-April 1, 2023. A Deep-learning Natural Language Processing Algorithm to Improve Keyword-Based Identification of Patients with Alzheimer’s Disease from Electronic Health Records. 2023.
View 46 more publications: View full profile at BUMC