A Model to predict severity of drug-induced liver injury in humans.
about
Drug-induced liver injury: Towards early prediction and risk stratificationDrug-induced liver injury: recent advances in diagnosis and risk assessment.Drug-induced liver injury in inflammatory bowel disease: 1-year prospective observational studyA review of drug-induced liver injury databases.Highlights of drug - and herb- induced liver injury in the literature from 2016: how best to translate new information into clinical practice?Evaluation of DILI Predictive Hypotheses in Early Drug Development.The Liver Toxicity Knowledge Base (LKTB) and drug-induced liver injury (DILI) classification for assessment of human liver injury.N-acetylcysteine and prednisolone treatment improved serum biochemistries in suspected flupirtine cases of severe idiosyncratic liver injury.Drug-Induced Arrhythmia: Bridging the Gap Between Pathophysiological Knowledge and Clinical Practice.
P2860
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P2860
A Model to predict severity of drug-induced liver injury in humans.
description
2016 nî lūn-bûn
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2016年の論文
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2016年学术文章
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2016年学术文章
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2016年学术文章
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2016年学术文章
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2016年学术文章
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name
A Model to predict severity of drug-induced liver injury in humans.
@en
A Model to predict severity of drug-induced liver injury in humans.
@nl
type
label
A Model to predict severity of drug-induced liver injury in humans.
@en
A Model to predict severity of drug-induced liver injury in humans.
@nl
prefLabel
A Model to predict severity of drug-induced liver injury in humans.
@en
A Model to predict severity of drug-induced liver injury in humans.
@nl
P2860
P356
P1433
P1476
A Model to predict severity of drug-induced liver injury in humans.
@en
P2093
Jürgen Borlak
Minjun Chen
P2860
P304
P356
10.1002/HEP.28678
P407
P50
P577
2016-06-15T00:00:00Z