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)

Robotics & Machine Learning Daily News2024，Issue(Aug.27) ：82-83.

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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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Abstract

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.”

Key words

Guangzhou/People’s Republic of China/A sia/Chemometric/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024

Robotics & Machine Learning Daily News

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