摘要
机器人与机器学习的新闻编辑每日新闻-机器学习的新研究是一篇报道的主题。根据来自芬兰赫尔辛基的新闻报道和NewsRx记者的报道，研究表明：“由聚(2-oxazoline)s和poly(2-oxazine)s)组成的嵌段共聚物可以作为药物传递系统；它们形成了携带难溶于水药物的胶束。最近的许多研究都研究了聚合物结构变化和疏水性钙对药物负载的影响。”新闻记者从赫尔辛基大学的研究中引用了一句话：“在这项工作中，我们结合这些数据建立了一个扩展的配方数据库。测试了不同分子性质和指纹图谱作为配方特异性混合物描述符的适用性。针对不同描述符子集和加载效率和加载能力阈值，建立了各种分类和回归模型。”在交叉验证和外部验证中，最佳模型获得了总体良好的统计数据（BALA NCED准确度为0.8）。随后，对重要特征进行了剖析以进行解释，并对药物库进行了潜在的治疗应用案例筛选，这些聚合物可以用于开发疏水性DRU GS的新制剂。
Abstract
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 originating in Helsinki, Finl and, by NewsRx journalists, research stated, “Block copolymers, composed of poly (2-oxazoline)s and poly(2-oxazine)s, can serve as drug delivery systems; they fo rm micelles that carry poorly water-soluble drugs. Many recent studies have inve stigated the effects of structural changes of the polymer and the hydrophobic ca rgo on drug loading.” The news reporters obtained a quote from the research from the University of Hel sinki, “In this work, we combine these data to establish an extended formulation database. Different molecular properties and fingerprints are tested for their applicability to serve as formulation-specific mixture descriptors. A variety of classification and regression models are built for different descriptor subsets and thresholds of loading efficiency and loading capacity, with the best models achieving overall good statistics for both cross- and external validation (bala nced accuracies of 0.8). Subsequently, important features are dissected for inte rpretation, and the DrugBank is screened for potential therapeutic use cases whe re these polymers could be used to develop novel formulations of hydrophobic dru gs.”
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