10月22日：微软研究人员表示，根据周四发表在《科学》杂志上的一项研究，一种像医生那样逐步诊断患者的AI工具，在解决复杂医疗病例方面的准确率是普通医生的两倍多。
Oct 22 : Microsoft researchers say an AI tool that diagnoses patients step by step, as doctors do, was more than twice as accurate as general physicians at solving complex medical cases, according to a study published on Thursday in Science.
根据该报告，该模型利用一个“编排器”来识别和协调应向患者提出的问题，以及应安排的检查和测试，该编排器通过采用一个模拟临床专家小组协作解决诊断病例的方式，来组织AI如何解决问题。
The model identifies and coordinates the questions that should be asked of a patient, as well as the exams and tests that should be ordered, using an "orchestrator" that organizes how AI will tackle a problem by employing a simulated panel of clinical experts collaborating to solve diagnostic cases, according to the report.
现有的医疗AI模型通常采取一次性全盘考虑的方法，即检查患者的所有症状、实验室结果和影像学研究以生成诊断。
Existing medical AI models typically take an all-at-once approach that examines all of a patient's symptoms, lab results and imaging studies to generate a diagnosis.
研究负责人在接受采访时表示，在编排器协调诊断步骤的情况下，AI模型首先决定询问患者病史的哪些方面以及体格检查中什么是重要的。基于所获取的信息，它决定安排哪些检查，考虑结果，并根据需要安排进一步检查。在此期间，它不断更新其工作假设和计划。
With the orchestrator coordinating the steps to reaching a diagnosis, the AI model first decides what to ask about the patient’s history and what is significant in the physical exam. Based on what it learns, it decides which tests to order, considers the results, and orders further testing as appropriate. All the while, it is updating its working hypotheses and plans, the research leaders said in an interview.
在被要求诊断300多个高度罕见且令人困惑的医疗难题时，采用诊断编排器的模型在“诊疗工作”患者并确定诊断方面的准确率，是使用教科书和互联网的普通医生的两倍多。
Tasked with diagnosing more than 300 highly unusual and confusing medical dilemmas, the model employing the diagnostic orchestrator was more than twice as accurate at "working up" the patient and determining the diagnosis as general physicians using textbooks and the internet.
当面对源自一个主要急诊室入院数据库的场景时，该工具的表现也优于人类医生。
The tool also outperformed human physicians when presented with scenarios drawn from a major database of emergency room admissions.
研究人员表示，将这类旧系统与人类医生进行比较的评估通常使用选择题。
Assessments comparing these types of older systems to human doctors usually use multiple-choice questions, the researchers said.
微软AI健康部门企业副总裁多米尼克·金博士表示：“AI在这类测试中取得100%通过率已经变得非常擅长了。”他的团队正在开发这项新技术。
"AI has become very good at getting a 100 per cent pass rate on those,” said Dr. Dominic King, the corporate vice president of the health unit at Microsoft AI, whose team is developing the new technology.
“但当然，那并非现实世界。从未有患者带着一份漂亮的摘要来找我看病。”研究人员还发现，当由编排器设计检查方案时，诊断过程的成本比由人类医生设计时更低。
“But of course, that's not real-world. No patient ever came to see me with a nice summary.”The researchers also found that diagnostic processes cost less when the orchestrator designs the work-ups than when human doctors do.
“我们不仅在衡量系统的准确性，还在衡量它进行诊断检查的过程有多么审慎和周全，”微软AI健康部门负责人哈沙·诺里（Harsha Nori）表示。
“We're not just measuring the accuracy of the systems. We're also measuring how judiciously and carefully it goes through a diagnostic work-up,” said Harsha Nori, head of AI at Microsoft AI Health.
在与波士顿贝斯以色列女执事医疗中心的合作中，研究人员下一步将测试该工具在急诊科候诊区对患者进行分诊的能力。
In a collaboration with Beth Israel Deaconess Medical Center in Boston, the researchers will next test the tool’s ability to triage patients in emergency department waiting rooms.