There has been a rapidly growing interest in Automatic Symptom Detection (ASD) and Automatic Diagnosis (AD) systems in the machine learning research literature, aiming to assist doctors in telemedicine services. These systems are designed to interact with patients, collect evidence about their symptoms and relevant antecedents, and possibly make predictions about the underlying diseases. Doctors would review the interactions, including the evidence and the predictions, collect if necessary additional information from patients, before deciding on next steps. Despite recent progress in this area, an important piece of doctors' interactions with patients is missing in the design of these systems, namely the differential diagnosis. Its absence is largely due to the lack of datasets that include such information for models to train on. In this work, we present a large-scale synthetic dataset of roughly 1.3 million patients that includes a differential diagnosis, along with the ground truth pathology, symptoms and antecedents for each patient. Unlike existing datasets which only contain binary symptoms and antecedents, this dataset also contains categorical and multi-choice symptoms and antecedents useful for efficient data collection. Moreover, some symptoms are organized in a hierarchy, making it possible to design systems able to interact with patients in a logical way. As a proof-of-concept, we extend two existing AD and ASD systems to incorporate the differential diagnosis, and provide empirical evidence that using differentials as training signals is essential for the efficiency of such systems or for helping doctors better understand the reasoning of those systems.

翻译：在机器学习研究文献中,对自动症状检测(ASD)和自动诊断(AAD)系统的兴趣迅速增长,目的是协助医生进行远程医疗服务,这些系统旨在与病人互动,收集有关其症状和相关前兆的证据,并有可能对基本疾病作出预测。医生将审查这些相互作用,包括证据和预测,必要时在决定下一步之前从病人那里收集更多的信息。尽管最近在这方面取得了进展,但医生与病人互动的重要部分在设计这些系统时却缺少,即差别诊断。缺乏这些系统主要是因为缺乏数据集,其中包括用于培训模型的这类信息。在这项工作中,我们提供了大约130万病人的大规模合成数据集,其中包括差异诊断,还有地面真相病理学、症状和病理学,在决定下一步步骤之前从病人那里收集更多的信息。与现有的数据集不同,这个数据集还包含直截和多选的症状和病理特征。这些数据的缺失主要是由于缺少数据集,其中包含用于培训模型的这类信息。此外,有些症状可以被组织成一种系统,可以用来进行逻辑分析的系统。