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Deep reinforcement learning for personalized treatment recommendation
Mingyang Liu
,
Xiaotong Shen
,
Wei Pan
Statistics (Twin Cities)
Biostatistics
Research output
:
Contribution to journal
›
Article
›
peer-review
46
Scopus citations
Overview
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Dive into the research topics of 'Deep reinforcement learning for personalized treatment recommendation'. Together they form a unique fingerprint.
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Keyphrases
Treatment Recommendations
100%
Personalized Treatment
100%
Deep Reinforcement Learning (deep RL)
100%
Cancer Cell Lines
50%
Precision Medicine
50%
Supervised Learning
50%
Proximal Policy Optimization
50%
Patient-centered
25%
Effective Treatment
25%
Clinical Features
25%
Patient-specific
25%
Cancer Treatment
25%
Drug Response
25%
Chemical Compounds
25%
Recommender Systems
25%
Reinforcement Learning
25%
Machine Learning Approach
25%
Clinical Profile
25%
Line Data
25%
Molecular Profile
25%
Genomic Features
25%
Promising Treatment
25%
Predicted Effects
25%
Molecular Features
25%
Learning-based
25%
Ranking System
25%
Penalized Regression
25%
Markov Decision Process
25%
Large-scale Screening
25%
Advance Cancer
25%
Personalized Ranking
25%
Regression System
25%
Medicine and Dentistry
Personalized Medicine
100%
Cancer Cell Line
100%
Decision Making
50%
Cancer Therapy
50%
Clinical Feature
50%
Drug Response
50%
Cell Line
50%
Effective Treatment
50%
Computer Science
Deep Reinforcement Learning
100%
Supervised Learning
50%
Optimization Policy
50%
Precision Medicine
50%
Reinforcement Learning
25%
Recommender Systems
25%
Machine Learning Approach
25%
Markov Decision Process
25%
Simulated Data
25%
Individual Patient
25%
Proof
25%
Engineering
Deep Reinforcement Learning
100%
Proximal Policy Optimization
50%
Proof-of-Concept
25%
Learning Approach
25%
Simulated Data
25%
Patient Specific
25%
Line Data
25%
Individual Patient
25%
Reinforcement Learning
25%
Markov Decision Process
25%
Learning System
25%
Chemical Engineering
Deep Reinforcement Learning
100%
Supervised Learning
50%
Learning System
25%
Reinforcement Learning
25%
Cancer Therapy
25%
Pharmacology, Toxicology and Pharmaceutical Science
Malignant Neoplasm
100%
Clinical Feature
33%