---

Research Interests: Clinical Natural Language Processing; Artificial Intelligence (Machine/Deep Learning) Applications in Healthcare

Dr. Wang is vice chair of research and assistant professor with a primary appointment in the Department of Health Information Management, and secondary appointments in the Intelligent Systems Program, Department of Biomedical Informatics, Clinical and Translational Science Institute, UPMC Hillman Cancer Center, at the University of Pittsburgh. He also serves as the Chair of the American Medical Informatics Association (AMIA) Natural Language Processing Working Group, and the NLP Lead of the National Center for Advancing Translational Sciences (NCATS) Accrual to Clinical Trails (ACT) Network. He has over 10 years of research experience in artificial intelligence (AI), natural language processing (NLP), and machine learning methodologies and applications in health care. He is also a pioneer in applying generative AI and large language models (LLMs) in clinical NLP. His lab is one of the first to leverage these LLMs in zero-shot and few-shot settings for clinical purposes. Recently, Dr. Wang's research focus has shifted towards evaluation of the generative AI models and assessing the impact of generative AI in healthcare, with a particular interest in its evaluation and ethical implications. He is the original author of the GREAT PLEA ethical principles and QUEST evaluation framework for the use of generative AI in healthcare.

Biography » CV (Web)» CV (PDF)»

---

Selected Publications All Publications»

Google Scholar   ResearchGate

• Thomas Yu Chow Tam, Sonish Sivarajkumar, Sumit Kapoor, Alisa V. Stolyar, Katelyn Polanska, Karleigh R. McCarthy, Hunter Osterhoudt, Xizhi Wu, Shyam Visweswaran, Sunyang Fu, Piyush Mathur, Giovanni E. Cacciamani, Cong Sun, Yifan Peng, Yanshan Wang. A framework for human evaluation of large language models in healthcare derived from literature review. npj Digital Medicine 7, no. 1 (2024): 258.
• David Oniani, Jordan Hilsman, Yifan Peng, Ronald K. Poropatich, Jeremy C. Pamplin, Gary L. Legault, Yanshan Wang. Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare. npj Digital Medicine 6, no. 1 (2023): 225.
• Sonish Sivarajkumar, Yufei Huang, Yanshan Wang. Fair patient model: Mitigating bias in the patient representation learned from the electronic health records. Journal of Biomedical Informatics, Vol. 148, 2023.
• David Oniani, Sreekanth Sreekumar, Renuk DeAlmeida, Dinuk DeAlmeida, Vivian Hui, Young Ji Lee, Yiye Zhang, Leming Zhou, Yanshan Wang. Towards Improving Health Literacy in Patient Education Materials with Neural Machine Translation Models. AMIA Informatics Summit. 2023.
• Hunter Osterhoudt, Courtney E. Schneider, Haneef A. Mohammad, Minmei Shih, Alexandra E. Harper, Leming Zhou, Elizabeth R. Skidmore, Yanshan Wang. Automated Fidelity Assessment for Strategy Training in Inpatient Rehabilitation using Natural Language Processing. AMIA Informatics Summit. 2023.
• Sonish Sivarajkumar, Yanshan Wang. HealthPrompt: A Zero-shot Learning Paradigm for Clinical Natural Language Processing. AMIA 2022 Annual Symposium. 2022. [ Best Student Paper Finalist]
• David Oniani, Bambang Parmanto, Andi Saptono, Allyn Bove, Janet Freburger, Shyam Visweswaran, Nickie Cappella, Brian McLay, Jonathan C Silverstein, Michael J Becich, Anthony Delitto, Elizabeth Skidmore, Yanshan Wang. ReDWINE: A clinical datamart with text analytical capabilities to facilitate rehabilitation research. International Journal of Medical Informatics 177 (2023): 105144.
• Oniani, David, Premkumar Chandrasekar, Sonish Sivarajkumar, Yanshan Wang. Few-Shot Learning for Clinical Natural Language Processing Using Siamese Neural Networks: Algorithm Development and Validation Study. JMIR AI 2 (2023): e44293.

All Publications »

---

Honors and Media Coverage More »

• Ethical healthcare AI in 8 mnemonic elements
• 'GREAT PLEA' system proposed for responsible use of generative AI in healthcare
• How Pitt researchers are using AI to help stroke patients
• Can AI Help Address the Effects of Health Inequities?
• Our Researchers are Using Health Informatics Technologies to Improve Patient Care
• Fellow of AMIA (FAMIA)

---

Teaching More »

Courses

• HI 2020 Practical Statistics & Programming Using Python and R
• HI 2250 Foundations of Health Informatics

Lectures and Tutorials

• Tutorial Methods and Applications of Natural Language Processing in Medicine. International Conference on Artificial Intelligence in Medicine (AIME), Minneapolis, MN (Virtual due to COVID), August 25, 2020.(Slides)
• Lecture A Simple Introduction to Natural Language Processing and Its Clinical Applications in the Era of Artificial Intelligence. South Dakota State University Data Science Symposium, February, 2020.(Abstract)
• Tutorial Applications of Natural Language Processing in Clinical Research and Practice. The 2019 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Minneapolis, MN, 2019.(Slides)
• Tutorial RNN / LSTM Architectures and their applications in clinical note analytics, OSCT Annual Meeting: Deep Learning Foundation and Application with a Special Focus on Medical Informatics, Milwaukee, WI, May 6, 2019.(Video)

---

Funding More »

My research is supported by federal goverments, research institutions, and companies:

• NLM R01. Closing the loop with an automatic referral population and summarization system.
• NCATS. ENACT: Translating Health Informatics Tools to Research and Clinical Decision Making. (Role: NLP Lead, Co-I)
• SHRS Dean Award. Precision Rehabilitation. (Role: PI)
• CTSI Awards. A3ST – AI Based Automated Fidelity Assessment for Strategy Training in Inpatient Rehabilitation. (Role: PI)
• Pitt Momentum Funds. Improving Health Equity by Analyzing Social Determinants of Health from the Electronic Health Records. (Role: PI)
• The Year of Data and Society Award. Understanding Bias in Big Data and Artificial Intelligence for Health Care Through an Educational Health Informatics Hackathon. (Role: PI)
• CHECE Research Award. Developing Artificial Intelligence Models to Automatically Identify Social Determinants of Health Among Minority Populations from the Electronic Health Records and to Provide Implications for Health Equity. (Role: PI)
• NIH NLM-R01. Semi-structured Information Retrieval in Clinical Text for Cohort Identification. (Role: Co-I)
• NIH NCATS-UL1. Supplement Investigation of Chronic Pain Management Based on Electronic Health Records. (Role: Co-I)
• NIH NMH-R01. Leveraging EHR-linked biobanks for deep phenotyping, polygenic risk score modeling, and outcomes analysis in psychiatric disorders. (Role: Co-I)
• NIH NINDS-R01. Enabling Comparative Effectiveness Research in Silent Brain Infarction Through Natural Language Processing and Big Data. (Role: Co-I)

---

Professional Service More »

• Editorial: Biomedical Informatics Insights, Frontiers in AI, MedInfo
• Journal Reviewer: Journal of Biomedical Informatics, Journal of American Medical Informatics Association, Journal of Medical Internet Research, International Journal of Medical Informatics, Knowledge-Based Systems, Neurocomputing, Plos One, Applied Clinical Informatics, Journal of Medical Internet Research, Journal of Healthcare Informatics Research, IEEE Transactions on Neural Networks and Learning Systems, Pharmaceutical Medicine, Nucleic Acids Research.
• Conference Reviewer: COLING, EMNLP, ACL, ACM-BCB, IEEE-BIBM, IEEE-ICHI, AMIA, AMIA-CRI, AMIA Joint Summits on Translational Science, AMIA Annual Symposium, HEALTHINFO, BIOTECHNO, SEPDA, ICIBM.
• PC member: ICHI, BIOTECHNO, NAACL, NLPCC, IHKDM, KDTBI, BIOTECHNO, LREC.
• Chair and Steering committee: HealthNLP Workshop 2018, 2019, 2020, 2021.
• Organizer: BioCreative/OHNLP 2018 Challenge, 2019 n2c2/OHNLP Challenge.