摘要
机器人与机器学习每日新闻的新闻记者兼工作人员新闻编辑发布了关于人工智能的新研究结果。根据NewsRx Co Rresponders来自挪威特罗姆索的新闻，研究表明，"机器学习(ML)Healt Hcare和药物相关研究中的预测模型在编码高维AL Health编码系统(HCSs)方面面临挑战，如ICD、ATC和DRG代码。给出了模型降维与信息损失最小化之间的距离，探讨了利用网络分析模块化方法对HCS进行分组，提高ML模型的编码效率。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New study results on artificial intelligence have been published. According to news originating from Tromso, Norway, by NewsRx co rrespondents, research stated, “Machine learning (ML) prediction models in healt hcare and pharmacy-related research face challenges with encoding high-dimension al Healthcare Coding Systems (HCSs) such as ICD, ATC, and DRG codes, given the t rade-off between reducing model dimensionality and minimizing information loss. To investigate using Network Analysis modularity as a method to group HCSs to im prove encoding in ML models.”
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NSTL