Medical Decision Making in Rare Disease

由临床标记物、笔记和患者报告结果(PROM)补充的数据驱动系统能否预测罕见疾病的临床干预需求？这与传统的稳定性标记物相比表现如何？2.我们能否整合医学领域知识以更好地在算法中表示医疗干预的结构？1换句话说，我们如何将人类专家知识转化为机器智能，以及数据驱动的智能如何转化并与人类理解兼容？

Can data-driven systems supplemented by clinical markers, notes and Patient-Reported Outcomes (PROMs) predict the need for a clinical intervention in rare diseases? How does this perform against traditional stability markers? 2. Can we integrate medical domain knowledge to better represent the structure of medical interventions in algorithms?1 In other words, how do we translate human expert knowledge into machine intelligence and how data driven intelligence can be translated and compatible with human understanding?