Jinying Chen PhD

Assistant Professor, Preventive Medicine & Epidemiology

72 E. Concord Street | (732) 668-7728
Jinying Chen

Preventive Medicine & Epidemiology


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 vice 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:

Novel Applications of NLP and Machine Learning in Health 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. Since joining BU, she 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.

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.


Computer Science, PhD, University of Pennsylvania, 2006

Computer Science, MS, University of Pennsylvania, 2001

Computer Science, ME/MEng, Tsinghua University, 2000

Computer Science, BS, Tsinghua University, 1998


Published on 3/7/2022

Chen J, Wijesundara JG, Enyim GE, Lombardini LM, Gerber BS, Houston TK, Sadasivam RS. Understanding Patients' Intention to Use Digital Health Apps That Support Postdischarge Symptom Monitoring by Providers Among Patients With Acute Coronary Syndrome: Survey Study. JMIR Hum Factors. 2022 Mar 07; 9(1):e34452. PMID: 35254269.

Published on 3/1/2022

Houston TK, Chen J, Amante DJ, Blok AC, Nagawa CS, Wijesundara JG, Kamberi A, Allison JJ, Person SD, Flahive J, Morley J, Conigliaro J, Mattocks KM, Garber L, Sadasivam RS. Effect of Technology-Assisted Brief Abstinence Game on Long-term Smoking Cessation in Individuals Not Yet Ready to Quit: A Randomized Clinical Trial. JAMA Intern Med. 2022 Mar 01; 182(3):303-312. PMID: 35072714.

Published on 1/1/2022

Constance Owens, Rachel Gold, Jinying Chen, Ran Xu, Heather Angier, Amy G. Huebschmann, Huebschmann, Mayuko Ito Fukunaga, Krisda H. Chaiyachati, Katharine Rendle, Kimberly Robien, Lisa DiMartino, Daniel J. Amante, Jamie Faro, Maura Kepper, Alex Ramsey, Eric Bressman. AMIA 2022 Annual Symposium. Implementation of Health Information Technology (HIT) Approaches for Secondary Cancer Prevention in Primary Care: A Scoping Review. 2022.

Published on 1/1/2022

Constance Owens, Jinying Chen, Ren Xu, Heather Angier, Amy G. Huebschmann, Mayuko Ito Fukunaga, Krisda H. Chaiyachati, Katharine Rendle, Kimberly Robien, Lisa DiMartino, Daniel J. Amante, Jamie Faro, Maura Kepper, Alex Ramsey, Eric Bressman, Rachel Gold. Society for Implementation Research Collaboration Conference. Implementation of Health Information Technology for Secondary Cancer Prevention in Primary Care: A Scoping Review. 2022.

Published on 1/1/2022

Jinying Chen, Sarah Cutrona, Ajay Dharod, Adam Moses, Aaron Bridges, Brian Ostasiewski, Kristie L. Foley, Thomas K. Houston. "Emerging Research Areas in Building the Future of D&I Science" Session at the 15th Annual Conference on the Science of Dissemination and Implementation in Health (D&I 2022). Monitoring for unintended consequences of EHR-based implementation strategies: A novel approach using EHR audit logs and machine learning. 2022.

Published on 1/1/2022

Jinying Chen, Sarah L. Cutrona, Ajay Dharod, Aaron Bridges, Adam Moses, Brian Ostasiewski, Kristie L. Foley, Thomas K. Houston. AMIA 2022 Annual Symposium. Characterizing Clinical Activity Patterns by Topics Inferred from Electronic Health Record Audit Logs. 2022.

Published on 9/28/2021

Chen J, Wijesundara JG, Patterson A, Cutrona SL, Aiello S, McManus DD, McKee MD, Wang B, Houston TK. Facilitators and barriers to post-discharge pain assessment and triage: a qualitative study of nurses' and patients' perspectives. BMC Health Serv Res. 2021 Sep 28; 21(1):1021. PMID: 34583702.

Published on 9/26/2021

Chen J, Houston TK, Faro JM, Nagawa CS, Orvek EA, Blok AC, Allison JJ, Person SD, Smith BM, Sadasivam RS. Evaluating the use of a recommender system for selecting optimal messages for smoking cessation: patterns and effects of user-system engagement. BMC Public Health. 2021 Sep 26; 21(1):1749. PMID: 34563161.

Published on 8/9/2021

Chen J, Kiefe CI, Gagnier M, Lessard D, McManus D, Wang B, Houston TK. Non-specific pain and 30-day readmission in acute coronary syndromes: findings from the TRACE-CORE prospective cohort. BMC Cardiovasc Disord. 2021 Aug 09; 21(1):383. PMID: 34372783.

Published on 1/1/2021

Jinying Chen, Mayuko ItoFukunaga, Evan Jones, Kavitha Balakrishnan, Sarah L. Cutrona. The 2021 SGIM Annual Meeting (Virtual SGIM2021 Conference). A natural language processing system to extract COVID-19 symptoms from electronic health records. 2021.

View full list of 44 publications.