Virtual Seminar: Brian Denton (University of Michigan)
Predictive Models for Optimizing Imaging Decisions for Detection of Metastatic Prostate Cancer
Department of Industrial and Operations Engineering and
Department of Urology (by courtesy)
University of Michigan
Data-analytics approaches were used to develop, calibrate, and validate predictive models to help urologists in a large state-wide collaborative make prostate cancer staging decisions on the basis of individual patient risk factors. The models developed predict the probability a patient who receives radiographic imaging will have metastatic cancer. The models were developed using observational data for patients diagnosed with prostate cancer. The group experimented with a variety of machine learning methods and compared their performance at predicting outcomes of imaging. The models were validated using statistical methods based on bootstrapping and subsequent evaluation on out-of-sample data. These models were used to design guidelines that seek to optimally weigh the benefits and harms of radiological imaging for detection of metastatic prostate cancer. The Michigan Urological Surgery Improvement Collaborative, a state-wide medical collaborative, implemented these guidelines, which were predicted to reduce unnecessary imaging by more than 40% and limit the percentage of patients with missed metastatic disease to be less than 1%. The effects of the guidelines were measured post-implementation to confirm their impact on reducing unnecessary imaging across the state of Michigan.
Brian Denton’s research interests are in data-driven sequential decision making and optimization under uncertainty with applications to medicine. He is Chair of the Department of Industrial and Operations Engineering and he has a cross-appointment in the School of Medicine at University of Michigan. Before joining the University of Michigan he worked at IBM, Mayo Clinic, and North Carolina State University. He has co-authored more than 100 journal articles, conference proceedings, book chapters, and patents. He is past Chair of the INFORMS Health Applications Section, past Secretary of INFORMS, and past President of INFORMS.
Please contact carla diaz to obtain access to the seminar
All graduate seminars hosted by the Department of Civil and Systems Engineering are FREE and open to the public. Attendance is required for all enrolled CaSE graduate students.