A framework for evaluating sequential clinical interventions with disease progression.
This work proposes to leverage an advanced modeling technique, namely Markov Decision Process, to evaluate sequential clinical interventions in disease management. We have demonstrated our evaluation framework on a diabetes case study over two real data sets, and discovered valuable clinical insights towards better interventions during disease progression.
IBM Research -China.
Jing
J
Mei
Haifeng
H
Liu
Weijia
W
Shen
Wen
W
Sun
Gang
G
Hu
Guotong
G
Xie
Yue
Y
Pan
D003198:Computer Simulation; D019091:Critical Pathways / Q000706:statistics & numerical data*; D020000:Decision Support Systems, Clinical; D003661:Decision Support Techniques; D003920:Diabetes Mellitus / Q000175:diagnosis* / Q000188:drug therapy*; D018450:Disease Progression; D006801:Humans; D008390:Markov Chains; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care / Q000379:methods / Q000706:statistics & numerical data*; D011379:Prognosis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity