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Learning optimal biomarker-guided treatment policy for chronic disorders
Bin Yang
, Xingche Guo
,
Ji Meng Loh
, Qinxia Wang
, Yuanjia Wang
Mathematical Sciences
Research output
:
Contribution to journal
›
Article
›
peer-review
2
Scopus citations
Overview
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Dive into the research topics of 'Learning optimal biomarker-guided treatment policy for chronic disorders'. Together they form a unique fingerprint.
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Keyphrases
Chronic Disorders
100%
Guided Therapy
100%
Treatment Policy
100%
Average Treatment Effect
50%
Non-invasive Measurement
25%
Treatment Assignment
25%
Integrated pipeline
25%
Preprocessing pipeline
25%
Effect Modifier
25%
Randomized Controlled Clinical Trial
25%
Conditional Average Treatment Effect
25%
Causal Forest
25%
Alpha Frequency Band
25%
EMBARC
25%
Optimal Depth
25%
Outcome-based Learning
25%
Policy Learning
25%
Psychology
Chronic Disorder
100%
Electroencephalogram
100%
Resting-State
16%
Depression
16%
Learning Algorithm
16%
Neuroscience
Electroencephalogram
100%
Major Depressive Disorder
16%
Antidepressant
16%
Biochemistry, Genetics and Molecular Biology
Controlled Clinical Trial
16%