Optimizing active surveillance for prostate cancer using partially observable Markov decision processes

W Li, BT Denton, TM Morgan - European Journal of Operational Research, 2023 - Elsevier
We describe a finite-horizon partially observable Markov decision process (POMDP)
approach to optimize decisions about whether and when to perform biopsies for patients on …

A data-driven framework to deal with intrinsic variability of industrial processes: An application in the textile industry

P Lajoie, J Gaudreault, N Lehoux, MB Ali - IFAC-PapersOnLine, 2019 - Elsevier
In many industries (eg natural resources processing, food processing, etc.), variation is
intrinsic to the process. Data captured by advanced technologies and sensors can drive in …

Optimization of Biomarker-Based Prostate Cancer Screening Policies

CL Barnett, BT Denton - … for Analytics-driven Improvements in a …, 2022 - books.google.com
Cancer screening has the potential to improve patient survival and lower the cost of
treatment by detecting cancer at an early stage when health outcomes are most favorable for …

Data-Driven Optimization for Individualized Medical Decision-Making in Cancer

W Li - 2021 - deepblue.lib.umich.edu
Cancer is one of the leading causes of death in many countries, including the United States.
Medical decision-making in cancer detection and treatment is often a challenging …

Stochastic Models for Improving Screening and Surveillance Decisions for Prostate Cancer Care

C Barnett - 2017 - deepblue.lib.umich.edu
Recent advances in the development of new technologies for the early detection and
treatment of cancer have the potential to improve patient survival and lower the cost of …

[引用][C] Literature Review of Healthcare Delivery

M Green, HB Nembhard - 2009 - State College, PA: Penn State …