Paper Info
Title
Markov Decision Process Modeling For Multi-Stage Optimization Of Intervention And Treatment Strategies In Breast Cancer
Abstract
The breast cancer is a prevalent problem that undermines quality of patients' lives and causes significant impacts on psychosocial wellness. Advanced sensing provides unprecedented opportunities to develop smart cancer care. The available sensing data captured from individuals enable the extraction of information pertinent to the breast cancer conditions to construct efficient and personalized intervention and treatment strategies. This research develops a novel sequential decision-making framework to determine optimal intervention and treatment planning for breast cancer patients. We design a Markov decision process (MDP) model for both objectives of intervention and treatment costs as well as quality adjusted life years (QALYs) with the data-driven and state-dependent intervention and treatment actions. The state space is defined as a vector of age, health status, prior intervention, and treatment plans. Also, the action space includes wait, prophylactic surgery, radiation therapy, chemotherapy, and their combinations. Experimental results demonstrate that prophylactic mastectomy and chemotherapy are more effective than other intervention and treatment plans in minimizing the expected cancer cost of 25 to 60 years-old patient with in-situ stage of cancer. However, wait policy leads to an optimal quality of life for a patient with the same state. The proposed MDP framework can also be generally applicable to a variety of medical domains that entail evidence-based decision making.
Year
DOI
Venue
2020
10.1109/EMBC44109.2020.9175905
42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20
Keywords
DocType
Volume
Breast cancer, Markov decision process, optimal treatment and intervention strategies, data-driven modeling
Conference
2020
ISSN
Citations 
PageRank 
1557-170X
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Farhad Imani193.44
Zihang Qiu200.34
Hui Yang32110.77