首页|Pontificia Universidade Catolica do Rio de Janeiro Reports Findings in Machine L earning (Identifying Substructures That Facilitate Compounds to Penetrate the Bl ood-Brain Barrier via Passive Transport Using Machine Learning Explainer Models)
Pontificia Universidade Catolica do Rio de Janeiro Reports Findings in Machine L earning (Identifying Substructures That Facilitate Compounds to Penetrate the Bl ood-Brain Barrier via Passive Transport Using Machine Learning Explainer Models)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting out of Rio de Janeiro, Brazil , by NewsRx editors, research stated, “The local interpretable model-agnostic ex planation (LIME) method was used to interpret two machine learning models of com pounds penetrating the blood-brain barrier. The classification models, Random Fo rest, ExtraTrees, and Deep Residual Network, were trained and validated using th e blood-brain barrier penetration dataset, which shows the penetrability of comp ounds in the blood-brain barrier.”
Rio de JaneiroBrazilSouth AmericaB lood Brain BarrierBlood-Brain BarrierBrain ResearchCentral Nervous SystemCyborgsEmerging TechnologiesHealth and MedicineMachine Learning
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