Development of Decision Forest Models for Prediction of Drug-Induced Liver Injury in Humans Using A Large Set of FDA-approved Drugs
Author:
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
http://www.nature.com/articles/s41598-017-17701-7.pdf
Reference49 articles.
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3. Chen, M. et al. Quantitative structure-activity relationship models for predicting drug-induced liver injury based on FDA-approved drug labeling annotation and using a large collection of drugs. Toxicol Sci 136, 242–249, https://doi.org/10.1093/toxsci/kft189 (2013).
4. Chen, M., Borlak, J. & Tong, W. High lipophilicity and high daily dose of oral medications are associated with significant risk for drug‐induced liver injury. Hepatology 58, 388–396, https://doi.org/10.1002/hep.26208 (2013).
5. Liu, Z. et al. Translating clinical findings into knowledge in drug safety evaluation-drug induced liver injury prediction system (DILIps). PLoS Comput Biol 7, e1002310, https://doi.org/10.1371/journal.pcbi.1002310 (2011).
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