论文标题
临床推荐系统：通过神经网络组成预测医学专业诊断选择
Clinical Recommender System: Predicting Medical Specialty Diagnostic Choices with Neural Network Ensembles
论文作者
论文摘要
对临床专业知识和设施等关键医疗资源的需求不断增长，促使基于人工智能（AI）的决策支持系统的出现。我们解决了预测专业推荐的临床检查的问题。作为手动创建的临床清单的替代方法，我们提出了一个数据驱动的模型，该模型建议基于患者从电子健康记录（EHR）中提取的最新临床记录提出必要的诊断程序。这有可能使卫生系统及时扩大对患者的初始医学专业诊断检查的访问。所提出的方法基于馈送前向神经网络的合奏，与常规临床清单相比，精度明显更高。
The growing demand for key healthcare resources such as clinical expertise and facilities has motivated the emergence of artificial intelligence (AI) based decision support systems. We address the problem of predicting clinical workups for specialty referrals. As an alternative for manually-created clinical checklists, we propose a data-driven model that recommends the necessary set of diagnostic procedures based on the patients' most recent clinical record extracted from the Electronic Health Record (EHR). This has the potential to enable health systems expand timely access to initial medical specialty diagnostic workups for patients. The proposed approach is based on an ensemble of feed-forward neural networks and achieves significantly higher accuracy compared to the conventional clinical checklists.
