The application of machine learning techniques as an adjunct to clinical decision making in alcohol dependence treatment.
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Predictive modeling of addiction lapses in a mobile health applicationHow well can post-traumatic stress disorder be predicted from pre-trauma risk factors? An exploratory study in the WHO World Mental Health SurveysComputational neuroscience approach to biomarkers and treatments for mental disorders.Predictors of heavy drinking during and following treatmentIndividualized relapse prediction: Personality measures and striatal and insular activity during reward-processing robustly predict relapse.Identifying Future Drinkers: Behavioral Analysis of Monkeys Initiating Drinking to Intoxication is Predictive of Future Drinking Classification.e-Addictology: An Overview of New Technologies for Assessing and Intervening in Addictive Behaviors.Towards enhanced metabolomic data analysis of mass spectrometry image: Multivariate Curve Resolution and Machine Learning
P2860
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P2860
The application of machine learning techniques as an adjunct to clinical decision making in alcohol dependence treatment.
description
2007 nî lūn-bûn
@nan
2007年の論文
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2007年学术文章
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2007年学术文章
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2007年学术文章
@zh-hans
2007年学术文章
@zh-my
2007年学术文章
@zh-sg
2007年學術文章
@yue
2007年學術文章
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2007年學術文章
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name
The application of machine lea ...... alcohol dependence treatment.
@en
The application of machine lea ...... alcohol dependence treatment.
@nl
type
label
The application of machine lea ...... alcohol dependence treatment.
@en
The application of machine lea ...... alcohol dependence treatment.
@nl
prefLabel
The application of machine lea ...... alcohol dependence treatment.
@en
The application of machine lea ...... alcohol dependence treatment.
@nl
P2093
P2860
P1476
The application of machine lea ...... alcohol dependence treatment.
@en
P2093
P2860
P304
P356
10.1080/10826080701658125
P577
2007-01-01T00:00:00Z