摘要
一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-人工智能的新研究是一篇报道的主题。根据NewsRx记者来自荷兰马斯特里海峡的新闻报道，研究表明：“在未来可能发生的大流行病中，我们研究了COVID-19疫情带来的挑战和机遇。本分析强调了人工智能(AI)和预测模型如何支持患者和临床医生管理随后的传染病，以及立法者和决策者如何支持这些努力。”将学习保健系统(LHS)从指南引入到R eal-world的实施中。新闻记者引用了马斯特里赫特大学医学中心的研究，“这篇报道记录了COVID-19大流行的轨迹，”强调在整个过程中产生的不同数据集。我们提出了通过人工智能和预测模型利用这些数据的策略，以增强LHS的功能。在这场前所未有的危机中，全世界患者和医疗保健系统所面临的挑战本可以通过知情和及时地采用LHS的三大支柱来缓解：知识，数据和实践。通过利用人工智能和预测性分析，我们可以开发工具，不仅可以在早期发现潜在的大流行倾向疾病，还可以帮助患者管理，提供决策支持，提供治疗建议，提供患者结果分流，预测康复后的长期疾病影响，监测病毒突变和变异出现，并实时评估疫苗和治疗效果。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating in Maastri cht, Netherlands, by NewsRx journalists, research stated, "In anticipation of po tential future pandemics, we examined the challenges and opportunities presented by the COVID-19 outbreak. This analysis highlights how artificial intelligence (AI) and predictive models can support both patients and clinicians in managing subsequent infectious diseases, and how legislators and policymakers could suppo rt these efforts, to bring learning healthcare system (LHS) from guidelines to r eal-world implementation." The news reporters obtained a quote from the research from Maastricht University Medical Center, "This report chronicles the trajectory of the COVID-19 pandemic , emphasizing the diverse data sets generated throughout its course. We propose strategies for harnessing this data via AI and predictive modelling to enhance t he functioning of LHS. The challenges faced by patients and healthcare systems a round the world during this unprecedented crisis could have been mitigated with an informed and timely adoption of the three pillars of the LHS: Knowledge, Data and Practice. By harnessing AI and predictive analytics, we can develop tools t hat not only detect potential pandemic-prone diseases early on but also assist i n patient management, provide decision support, offer treatment recommendations, deliver patient outcome triage, predict post-recovery long-term disease impacts , monitor viral mutations and variant emergence, and assess vaccine and treatmen t efficacy in real-time."
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