摘要
机器人与机器学习每日新闻的一位新闻记者兼新闻编辑发表了关于人工智能的新研究结果。根据NewsRx记者来自加州斯坦福的新闻，研究表明："临床预测模型的目的是预测罕见的、高风险的事件，但建立这种模型需要Robus T对不平衡数据集的理解及其独特的研究设计考虑。"我们的新闻记者从斯坦福大学的研究中获得了一句话：“本实用指南强调了外科数据科学家和遇到临床预测模型的读者的基本预测模型原则，”从特征工程和算法选择策略来评估模型，以及针对不平衡数据集的设计技术。我们通过一个使用可读代码的临床例子来强调基于机器学习的预测模型开发中的重要考虑因素和常见缺陷。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intell igence have been published. According to news originating from Stanford, Califor nia, by NewsRx correspondents, research stated, “Clinical prediction models ofte n aim to predict rare, high-risk events, but building such models requires robus t understanding of imbalance datasets and their unique study design consideratio ns.” Our news journalists obtained a quote from the research from Stanford University : “This practical guide highlights foundational prediction model principles for surgeon-data scientists and readers who encounter clinical prediction models, fr om feature engineering and algorithm selection strategies to model evaluation an d design techniques specific to imbalanced datasets. We walk through a clinical example using readable code to highlight important considerations and common pit falls in developing machine learning-based prediction models.”
NETL
NSTL