首页|Beijing University of Technology Reports Findings in Machine Learning [High-throughput prediction of oral acute toxicity in Rat and Mouse of over 100,0 00 polychlorinated persistent organic pollutants (PC-POPs) by interpretable data fusion-driven ...]
Beijing University of Technology Reports Findings in Machine Learning [High-throughput prediction of oral acute toxicity in Rat and Mouse of over 100,0 00 polychlorinated persistent organic pollutants (PC-POPs) by interpretable data fusion-driven ...]
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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 from Beijing, Peo ple’s Republic of China, by NewsRx correspondents, research stated,“This study utilized available oral acute toxicity data in Rat and Mouse for polychlorinated persistent organicpollutants (PC-POPs) to construct data fusion-driven machine learning (ML) global models. Basedon atom-centered fragments (ACFs), the colle cted high-throughput data overcame the applicability limitations,enabling accur ate toxicity prediction for a wide range of PC-POPs series compounds using onlysingle models.”
BeijingPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine Learning
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