©2018 by Yiye Zhang.

Skyline New York

How can we use data and technology to reduce clinician burden in making decisions?


A central theme of my research is concerned with developing health informatics and data science algorithms that elicit actual healthcare practice patterns from data sources such as electronic health records (EHR), to provide data-driven evidence to inform clinical decision support. I am especially passionate about using my research to empower patients with chronic conditions whose data reflect their extremely complex long-term clinical needs.

 

News

  • Our work in predicting postpartum depression was presented at Frontier of AI-Assisted Care (FAC) Scientific Symposium.

  • I am honored to be awarded a K01 award on Career Development in Biomedical Informatics and Data Science by the National Library of Medicine. Excited to be working in such an exciting field!

  • Our R03 study on the ordering patterns of opioids funded by AHRQ has begun. Look forward to the next 2 years!

  • Our work on predicting postpartum depression was featured in APA News Room.

  • I was invited to speak at the 1st Biomedical Big Data Symposium at New York City College of Technology

  • This Allscripts blog mentioned my work on order set development using machine learning

  • Presented in CTECH Annual Meeting, Davis, CA, Nov 2018

  • Presented in AMIA 2018 Annual Symposium, San Francisco, CA, Nov 2018

  • Goutham Rao, Katherine Kirley, Paul Epner, Yiye Zhang, Victoria Bauer, Ying Zhou, Anthony Solomonides. Identifying, Analyzing, and Visualizing Diagnostic Paths for Patients with Non-Specific Abdominal Pain. Applied Clinical Informatics 2018 (accepted)

  • My presentation in  LinkedIn NYC Machine Learning and Data Science Meetup, Sep 2018

  • Presented "Developing and Maintaining Clinical Decision Support Using Clinical Knowledge and Machine Learning: The Case of Order Sets " at Machine Learning in Medicine. Ithaca, NY. Sep 2018

  • Developing and maintaining clinical decision support using clinical knowledge and machine learning: the case of order sets (Journal of the American Medical Informatics Association, Aug 2018)

 

RESEARCH INTERESTS

Coming Soon

CLINICAL DECISION SUPPORT

Order Set

CLINICAL PATHWAYS

Health Trajectory

SOCIAL DETERMINANTS OF HEALTH

Built Environment

CHRONIC DISEASE

Chronic Kidney Disease, Heart Failure, Pain

 

PROFESSIONAL HISTORY

My Experience

ASSISTANT PROFESSOR

July 2016 -

Assistant Professor, Walsh McDermott Scholar in Public Health
Division of Health Informatics, Department of Health Policy and Research
Weill Cornell Medicine
Weill Cornell Graduate School of Medical Sciences
Cornell University, New York, NY

EDUCATION

April 2011 - March 2012

PhD     2011 – 2016                Information Systems and Management, Carnegie Mellon University

                                                (Thesis Committee: Rema Padman, PhD; Larry Wasserman, PhD; Ole Mengshoel, PhD) 

MS      2009 – 2011                Biostatistics, Columbia University

BA      2005 – 2009                Mathematics (major) & Biology (minor), Washington University in St. Louis

JOURNAL AND REFEREED CONFERENCE PROCEEDINGS

November 2009 - January 2011

  • Rao G, Kirley K, Epner P, Zhang Y, Bauer V, Padman R, Zhou Y, Solomonides A. Identifying, Analyzing, and Visualizing Diagnostic Paths for Patients with Nonspecific Abdominal Pain. Appl Clin Inform. 2018 Oct;9(4):905-913.

  • Zhang Y, Trepp R, Wang W, Luna J, Vawdrey DK, Tiase V. Developing and maintaining clinical decision support using clinical knowledge and machine learning: the case of order sets. J Am Med Inform Assoc. 2018 Aug 7.

  • Zhang Y, Padman R, Epner P, Bauer V, Solomonides A, Rao G. Identifying Diagnostic Paths for Undifferentiated Abdominal Pain from Electronic Health Record Data. AMIA Jt Summits Transl Sci Proc. 2018 May 18;2017:290-299.

  • Ancker JS, Kim MH, Zhang Y, Zhang Y, Pathak J. The potential value of social determinants of health in predicting health outcomes. J Am Med Inform Assoc. 2018 Aug 1;25(8):1109-1110.

  • Thomas D, Chung C, Zhang Y, Te A, Gratzke C, Woo H, Chughtai B. Clinical Trials in Benign Prostatic Hyperplasia: A Moving Target of Success. Eur Urol Focus. 2018 May 24.

  • Gartner D, Zhang Y, Padman R. Cognitive workload reduction in hospital information systems : Decision support for order set optimization. Health Care Manag Sci. 2018 Jun;21(2):224-243.

  • Zhang Y, John Richard Lee, Bilal Chughtai, Rema Padman. Variable selection for chronic disease outcome prediction using a causal inference technique: A preliminary study. 2018 IEEE International Conference on Healthcare Informatics, New York, NY, 2018

  • Zhang Y, Padman R. Data-driven Order Set Development Using Meta-Heuristic Optimization. 15th Conference on Artificial Intelligence in Medicine (AIME 2015). Pavia, Italy, 2015.

  • Zhang Y, Padman R, Wasserman L, Patel N, Teredesai P, Xie Q. On Clinical Pathway Discovery from Electronic Health Record Data. IEEE Intelligent Systems. 2015;30(1):70-5.

  • Gartner D, Zhang Y, Padman R. Workload Reduction Through Usability Improvement of Hospital Information Systems - The Case of Order Set Optimization. 36th International Conference on Information Systems (ICIS). Fort Worth, TX, 2015.

  • Zhang Y, Padman R, Levin JE. Paving the COWpath: data-driven design of pediatric order sets. Journal of American Medical Informatics Association (JAMIA). 2014 Oct;21(e2):e304-11.

  • Zhang Y, Padman R, L. Wasserman. On Learning and Visualizing Practice-based Clinical Pathways for Chronic Kidney Disease. American Medical Informatics Association (AMIA) 2014 Annual Symposium. Washington, DC, 2014. (2nd place, KDDM Student Paper Competition)

  • Zhang Y, Padman R, L. Wasserman. On Learning Clinical Pathways for Chronic Kidney Disease from Electronic Health Record Data: A Preliminary Graphical Approach. 2nd International Conference on Big Data and Analytics in Healthcare (BDAH). Singapore, 2014. (Best paper Runner-up)

  • Zhang Y, Padman R, Levin JE. Reducing Provider Cognitive Workload in CPOE use: Optimizing Order Sets. 14th World Congress on Health and Biomedical Informatics (MEDINFO). Copenhagen, Denmark, 2013. (Finalist, Student paper competition)

  • Zhang Y, Padman R, Levin JE. Toward Order Set Optimization Using Click Cost Criteria in the Pediatric Environment. 46th Hawaii International Conference on System Sciences (HICSS-46). Maui, HI, 2013.

  • Zhang Y, Padman R, Levin JE. Clustering Methods for Data-driven Order Set Development in the Pediatric Environment. 7th INFORMS Workshop on Data Mining and Healthcare Informatics. Phoenix, AZ, 2012.

  • Zhang Y, Padman R, Levin JE. Data-driven order set generation and evaluation in the pediatric environment. American Medical Informatics Association (AMIA) 2012 Annual Symposium. Chicago, IL, 2012. (Selected as ‘Hot Pick’ for the conference)

  • Yao L, Zhang Y, Li Y, Sanseau P, Agarwal P. Electronic health records: Implications for drug discovery. Drug Discovery Today. 2011 Jul;16(13-14):594-9.

HONORS AND AWARDS

June 2012 - May 2014

  • First Place, Weill Cornell Medicine BioVenture eLab Biomedical Business Plan Challenge, 2019

  • Walsh McDermott Scholar in Public Health, 2016-2019

  • Best Paper Award, International Conference on Decision Support System Technology 2016

  • Top rated poster, Mayo Clinic Delivery Science Summit, 2015

  • Doctoral Consortium at the 6th Annual Workshop on Health Information and Economics (WHITE), 2015

  • Honorable Mention, INFORMS Healthcare Poster Competition, 2015

  • Big Data Coursework for Computational Medicine (BDC4CM) Fellowship, 2015

  • Second place, American Medical Informatics Association (AMIA) Knowledge Discovery and Data Mining (KDDM) Student Paper Competition, 2014

  • Best Paper Runner Up, the 2nd International Conference on Big Data and Analytics in Healthcare (BDAH), 2014

  • Finalist, Student Paper Competition at the 14th World Congress on Health and Biomedical Informatics (MEDINFO), 2013

INVITED TALKS

April 2011 - March 2012

  • IBM Research, September 2016

  • Robert Smith School of Business, University of Maryland, College Park, 2017

  • Value Institute of New York Presbyterian Hospital, August 2016, March 2018

  • LinkedIn, September 2018

MENTORING

November 2009 - January 2011

Current and Past Mentoring:

  • Faezeh Movahedi (PhD candidate), Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh

  • Chensu Xie (PhD candidate), Tri-Institute PhD program in Computational Medicine, Weill Cornell Graduate School of Medical Sciences, Cornell University

  • Shuojia Wang (PhD candidate), Department of Epidemiology, Zhejiang University

  • Yonaka Harris, New York City College of Technology

 
Mail Boxes

GET IN TOUCH

I am looking for a research assistant to join my team!


Weill Cornell Medicine, Department of Healthcare Policy and Research, Division of Health Informatics

425 E 61st St
New York, New York County 10065
USA