The prediction approach of drug-induced liver injury: response to the issues of reproducible science of artificial intelligence in real-world applications
Chen Zhao, Yin Jiang, Xiaoyu Zhang, Rui Zheng, Ruijin Qiu, Yang Sun, Chen Zhao, Hongcai Shang
Abstract
In the previous study, we developed the generalized drug-induced liver injury (DILI) prediction model-ResNet18DNN to predict DILI based on multi-source combined DILI dataset and achieved better performance than that of previously published described DILI prediction models. Recently, we were honored to receive the invitation from the editor to response the Letter to Editor by Liu Zhichao, et al. We were glad that our research has attracted the attention of Liu's team and they has put forward their opinions on our research. In this response to Letter to the Editor, we will respond to these comments.
Topics & Concepts
Computer scienceDrug responseLiver injuryDrugLetter to the editorArtificial intelligenceMachine learningOperations researchData scienceMedicinePharmacologyPolitical scienceEngineeringLawDrug-Induced Hepatotoxicity and ProtectionComputational Drug Discovery MethodsPharmacovigilance and Adverse Drug Reactions