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(2018.1.22 14:30 N205)Jionghua (Judy) Jin:How Can Data Analytics Assist Clinical Decisions and Surgical Performance Assessment?
Update time: 2018-01-24


Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars


Jionghua (Judy) Jin, Professor of Industrial & Operations Engineering Department,Director of Manufacturing Program,The University of Michigan,

How Can Data Analytics Assist Clinical Decisions and Surgical Performance Assessment?
Time & Venue:
2018.1.22 14:30-15:30 N205
Massive healthcare and clinical data are widely collected from a variety of sources such as electronic health records, personal health monitoring devices and patient surveys, disease registries, etc. It is of increasing interests in utilizing those data to assist doctors’ or healthcare providers’ decisions. This presentation will use two examples to discuss some research challenges in data analytics for developing an evidence-based clinical decision support and surgical performance monitoring systems. Taking rotator cuff tears as the first example, some typical research challenges in analyzing clinical/healthcare data are presented. A general data analysis framework is proposed through integration of advanced data analytics methods, which include missing data imputation to handle heterogeneous mixed-type data, regularized variables selection for data dimension reduction, and probabilistic decision threshold for managing the decision risks due to inevitable false positive/negative errors. The second example is to discuss how to effectively assess and monitor cardiac surgical quality by considering the inevitable incoming health variations of patients who are under the surgery operations by different surgeons.


报告人简介:Jionghua (Judy) Jin is currently a professor in the Department of Industrial and Operations Engineering and the Director of Manufacturing Engineering Program at the University of Michigan. She received her BS and MS in Mechanical Engineering at Southeast University (Nanjing) in 1984 and 1987, and her PhD in Industrial and Operations Engineering at the University of Michigan in 1999, respectively.

Dr. Jin’s research focuses on developing new data analytics methodologies with broad applications in both manufacturing and service industries. She has received numerous awards including the NSF CAREER Award, the prestigious Presidential (PECASE) Award, and 11 Best Paper Awards since 2005, etc. She is currently a Departmental Editor for IIE Transactions, and was Vice President of INFORMS and the President of QCRE (Quality Control and Reliability Engineering) Division in Industrial Engineering (IE), and Chair of QSR (Quality, Statistics, and Reliability) Division in INFORMS. She is a Fellow of IIE and ASME, a senior member of ISI and ASQ, and a member of IEEE, INFORMS, and SME.



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