摘要
由一名新闻记者-机器人与机器学习每日新闻的工作人员新闻编辑-调查人员发布了关于人工智能的新报告。根据NewsRx记者来自印第安纳州西拉法耶特的新闻报道，研究表明，"在健康信息学领域，已经进行了广泛的研究，以预测疾病和从病人数据中获得额外的CT宝贵见解。"我们的新闻记者从普渡大学Y分校的研究中获得了一句话：“然而，在解决与数据收集相关的隐私问题方面存在着很大的差距。因此，迫切需要开发一种机器-安全认证模型，以无缝和连续地保护患者的数据，并在模型可能失败时找到潜在的解释。”我们提出了一种独特的方法，利用粗粒度心率数据计算出的新的特征心脏特征来保护患者数据，并利用各种统计和可视化技术来解释该模型的潜在漏洞，尽管从现成的心率数据中开发出性能合理的连续用户认证模型是可行的，但它们受到年龄和体重指数(BMI)等因素的影响。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news reporting originating from West Lafayet te, Indiana, by NewsRx correspondents, research stated, “In the field of health informatics, extensive research has been conducted to predict diseases and extra ct valuable insights from patient data.” Our news correspondents obtained a quote from the research from Purdue Universit y: “However, a significant gap exists in addressing privacy concerns associated with data collection. Therefore, there is an urgent need to develop a machine-le arning authentication model to secure the patients’ data seamlessly and continuo usly, as well as to find potential explanations when the model may fail. To addr ess this challenge, we propose a unique approach to secure patients’ data using novel eigenheart features calculated from coarse-grained heart rate data. Variou s statistical and visualization techniques are utilized to explain the potential vulnerabilities of the model. Though it is feasible to develop continuous user authentication models from readily available heart rate data with reasonable per formance, they are affected by factors such as age and Body Mass Index (BMI).”
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