首页|Jinan University Reports Findings in Machine Learning (Accurate Prediction of Ra t Acute Oral Toxicity and Reference Dose for Thousands of Polycyclic Aromatic Hy drocarbon Derivatives Based on Chemometric QSAR and Machine Learning)
Jinan University Reports Findings in Machine Learning (Accurate Prediction of Ra t Acute Oral Toxicity and Reference Dose for Thousands of Polycyclic Aromatic Hy drocarbon Derivatives Based on Chemometric QSAR and Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is th e subject of a report. According to newsreporting originating in Guangzhou, Peo ple’s Republic of China, by NewsRx journalists, research stated,“Acute oral tox icity is currently not available for most polycyclic aromatic hydrocarbons (PAHs ), especiallytheir derivatives, because it is cost-prohibitive to experimentall y determine all of them. Here, quantitativestructure-activity relationship (QSA R) models using machine learning (ML) for predicting the toxicity ofPAH derivat ives were developed, based on oral toxicity data points of 788 individual substa nces of rats.”
GuangzhouPeople’s Republic of ChinaA siaChemometricCyborgsEmerging TechnologiesMachine Learning
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