首页|Dalian University of Technology Reports Findings in Drug-Induced Liver Injury (Deep Learning Algorithm Based on Molecular Fingerprint for Prediction of Drug-Induced Liver Injury)
Dalian University of Technology Reports Findings in Drug-Induced Liver Injury (Deep Learning Algorithm Based on Molecular Fingerprint for Prediction of Drug-Induced Liver Injury)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
New research on Drugs and Therapies - Drug-Induced Liver Injury is the subject of a report. According to news reporting from Liaoning, People’s Republic of China, by NewsRx journalists, research stated, “Drug-induced liver injury (DILI) is one the rare adverse drug reaction (ADR) and multifactorial endpoints. Current preclinical animal models struggle to anticipate it, and in silico methods have emerged as a way with significant potential for doing so.” The news correspondents obtained a quote from the research from the Dalian University of Technology, “In this study, a high-quality dataset of 1573 compounds was assembled. The 48 classification models, which depended on six different molecular fingerprints, were built via deep neural network (DNN) and seven machine learning algorithms. Comparing the results of the DNN and machine learning models, the optional performing model was found as the one developed based on the DNN with ECFP_6 as input, which achieved the area under the receiver operating characteristic curve (AUC) of 0.713, balanced accuracy (BA) of 0.680, and F1 of 0.753. In addition, we used the SHapley Additive exPlanations (SHAP) algorithm to interpret the models, identified the crucial structural fragments related to DILI risk, and selected the top ten substructures with the highest contribution rankings to serve as warning indicators for subsequent drug hepatotoxicity screening studies.”
LiaoningPeople’s Republic of ChinaAsiaAlgorithmsCyborgsDigestive System Diseases and ConditionsDrug-Induced Liver InjuryDrugs and TherapiesEmerging TechnologiesHealth and MedicineLiver Diseases and ConditionsMachine Learning
NETL
NSTL
