datasheet2_A Comparison of Artificial Intelligence and Human Doctors for the Purpose of Triage and Diagnosis.pdf

AI virtual assistants have significant potential to alleviate the pressure on overly burdened healthcare systems by enabling patients to self-assess their symptoms and to seek further care when appropriate. For these systems to make a meaningful contribution to healthcare globally, they must be trusted by patients and healthcare professionals alike, and service the needs of patients in diverse regions and segments of the population. We developed an AI virtual assistant which provides patients with triage and diagnostic information. Crucially, the system is based on a generative model, which allows for relatively straightforward re-parameterization to reflect local disease and risk factor burden in diverse regions and population segments. This is an appealing property, particularly when considering the potential of AI systems to improve the provision of healthcare on a global scale in many regions and for both developing and developed countries. We performed a prospective validation study of the accuracy and safety of the AI system and human doctors. Importantly, we assessed the accuracy and safety of both the AI and human doctors independently against identical clinical cases and, unlike previous studies, also accounted for the information gathering process of both agents. Overall, we found that the AI system is able to provide patients with triage and diagnostic information with a level of clinical accuracy and safety comparable to that of human doctors. Through this approach and study, we hope to start building trust in AI-powered systems by directly comparing their performance to human doctors, who do not always agree with each other on the cause of patients’ symptoms or the most appropriate triage recommendation.

AI虚拟助手（AI virtual assistants）具备显著潜力，可通过帮助患者自主评估自身症状、并在适宜时机寻求进一步诊疗，以缓解过度承压的医疗体系的运行压力。若要让这类系统在全球医疗事业中发挥实质性作用，其必须同时获得患者与医疗从业者的信任，且需满足不同地区、不同人群的患者需求。我们研发了一款AI虚拟助手，可为患者提供分诊（triage）与诊断相关信息。尤为关键的是，该系统基于生成式模型（generative model），可通过相对简便的重新参数化操作，适配不同地区与人群的本土疾病及风险因子负担情况。这一特性颇具吸引力，尤其当我们考量AI系统在全球诸多地区，为发展中国家与发达国家优化医疗服务供给的潜力时。我们开展了一项前瞻性验证研究，评估该AI系统与人类医师的准确性与安全性。值得注意的是，我们针对完全一致的临床病例，分别独立评估了AI系统与人类医师的准确性与安全性；与以往研究不同的是，我们还同时考量了两类主体的信息收集流程。总体而言，我们发现该AI系统可为患者提供的分诊与诊断信息，其临床准确性与安全性可与人类医师相媲美。通过本研究与研究方法，我们希望通过直接将AI赋能系统的表现与人类医师进行对比，来逐步建立人们对这类系统的信任——毕竟人类医师之间，也并非总能就患者症状的病因或最恰当的分诊建议达成一致。