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An optimal policy for patient laboratory tests in intensive care units
Li Fang Cheng
, Niranjani Prasad
, Barbara E. Engelhardt
Computer Science
Center for Statistics & Machine Learning
Lewis-Sigler Institute for Integrative Genomics
Princeton Institute for Computational Science and Engineering
Research output
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Contribution to journal
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Conference article
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peer-review
26
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Dive into the research topics of 'An optimal policy for patient laboratory tests in intensive care units'. Together they form a unique fingerprint.
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Keyphrases
Optimal Policy
100%
Intensive Care Unit
100%
Lab Test
100%
Reward Function
50%
Laboratory Testing
25%
Procedural
25%
Function-based
25%
Dialysis
25%
Early Onset
25%
Action-based
25%
Lab Results
25%
Expected Utility
25%
Associated Costs
25%
Associated Risk
25%
Function Components
25%
Patient Management
25%
Clinical Decision-making
25%
Mechanical Ventilation
25%
Multiple Rewards
25%
Policy Learning
25%
Patient Care
25%
Test Wells
25%
Information Redundancy
25%
Composite Reward
25%
Clinical Goals
25%
Pareto Optimality
25%
Computer Science
Component Function
100%
Decision-Making
100%
Reinforcement Learning
100%
Pareto-optimality
100%
Information Redundancy
100%
Laboratory Test
100%
Pareto Optimality
100%
Mathematics
Tradeoff
100%
Optimal Policy
100%
Optimality
50%
Minimizes
50%
Component Function
50%
Clinical Decision
50%
Neuroscience
Reinforcement Learning
100%
Clinical Decision Making
100%
Mechanical Ventilation
100%
Biochemistry, Genetics and Molecular Biology
Laboratory Test
100%
Clinical Decision Making
16%
Economics, Econometrics and Finance
Pareto Efficiency
100%