摘要
一位新闻记者兼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编辑在德国科隆发表的新闻报道，研究表明，“实验室医学报告往往不能直观地为非医疗专业人员所理解。鉴于它们最近的优势、更容易获得以及在医疗许可考试中表现出色，因此患者很可能会求助于基于人工智能的CH机器人来了解他们的实验室结果。”我们的新闻记者从医学院和大学医院的研究中获得了一句话，“然而，评估这些聊天机器人在回答真实病人关于实验室医学的询问方面功效的实证研究很少。因此，这项调查包括了来自在线健康论坛的100个病人询问。”专门针对全血细胞计数的检测。其目的是评估三个基于CE的人工智能聊天机器人（ChatGPT、Gemini和Le Chat）的熟练程度，并与来自注册医生的在线反馈进行对比。结果显示，聊天机器人对实验室结果的解释不如来自在线医疗专业人员的解释。而聊天机器人表现出更高的移情沟通程度，他们经常对复杂的病人问题做出错误或过于笼统的回答。聊天机器人回答的适当性介于51%到64%之间。22%到33%的回答高估了患者的病情。一个值得注意的积极方面是聊天机器人一贯包含关于其非医疗性质的免责声明，以及寻求专业医疗建议的建议。聊天机器人对真实患者询问的实验室结果的解释突显了一种危险的二分法-感知到的可信度潜力，掩盖了事实的不准确性。
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 out of Cologne, German y, by NewsRx editors, research stated, “Laboratory medical reports are often not intuitively comprehensible to non-medical professionals. Given their recent adv ancements, easier accessibility and remarkable performance on medical licensing exams, patients are therefore likely to turn to artificial intelligence-based ch atbots to understand their laboratory results.” Our news journalists obtained a quote from the research from the Faculty of Medi cine and University Hospital, “However, empirical studies assessing the efficacy of these chatbots in responding to real-life patient queries regarding laborato ry medicine are scarce. Thus, this investigation included 100 patient inquiries from an online health forum, specifically addressing Complete Blood Count interp retation. The aim was to evaluate the proficiency of three artificial intelligen ce-based chatbots (ChatGPT, Gemini and Le Chat) against the online responses fro m certified physicians. The findings revealed that the chatbots’ interpretations of laboratory results were inferior to those from online medical professionals. While the chatbots exhibited a higher degree of empathetic communication, they frequently produced erroneous or overly generalized responses to complex patient questions. The appropriateness of chatbot responses ranged from 51 to 64 % , with 22 to 33 % of responses overestimating patient conditions. A notable positive aspect was the chatbots’ consistent inclusion of disclaimers regarding its non-medical nature and recommendations to seek professional medica l advice. The chatbots’ interpretations of laboratory results from real patient queries highlight a dangerous dichotomy - a perceived trustworthiness potentiall y obscuring factual inaccuracies.”
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