Maternal and child mortality is a public health problem that disproportionately affects low- and middle-income countries. Every day, 800 women and 6,700 newborns die from complications related to pregnancy or childbirth. And for every maternal death, about 20 women suffer serious birth injuries. However, nearly all of these deaths and negative health outcomes are preventable. Midwives are key to revert this situation, and thus it is essential to strengthen their capacities and the quality of their education. This is the aim of the Safe Delivery App, a digital job aid and learning tool to enhance the knowledge, confidence and skills of health practitioners. Here, we use the behavioral logs of the App to implement a recommendation system that presents each midwife with suitable contents to continue gaining expertise. We focus on predicting the click-through rate, the probability that a given user will click on a recommended content. We evaluate four deep learning models and show that all of them produce highly accurate predictions.
翻译：孕产妇和儿童死亡率是一个公共卫生问题,对中低收入国家的影响格外严重。每天有800名妇女和6 700名新生儿死于与怀孕或分娩有关的并发症。对于每一例孕产妇死亡,约有20名妇女遭受严重的分娩伤害。然而,几乎所有这些死亡和负面健康后果都是可以预防的。助产士是扭转这种状况的关键,因此,必须加强他们的能力和教育质量。这是安全分娩应用程序的目标,这是一个数字工作援助和学习工具,目的是提高保健从业人员的知识、信心和技能。在这里,我们利用App的行为记录系统实施一个建议系统,向每个助产士提供合适的内容,以继续获得专门知识。我们重点预测点击率,一个特定用户点击建议的内容的可能性。我们评估了四个深度学习模型,并显示所有这些模型都产生了非常准确的预测。
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