论文标题
可操作的手机健康追索权
Actionable Recourse via GANs for Mobile Health
论文作者
论文摘要
移动健康应用程序提供了收集可用于提供自适应干预措施的数据的独特方法。预测的结果极大地影响了此类干预措施的选择。通过反事实的追索权提供了修改用户预测的切实机制。通过确定有可能增加预期预测可能性的合理行动，利益相关者可以在他们的预测中获得代理。此外，追索权的机制可以实现反事实推理，可以帮助您洞悉因果介入特征的候选人。我们证明了GAN生成的追索权对基于合奏生存 - 分析的移动健康应用程序的可行性，该预测是针对熟练的亲生服务员的数字培训工具的中期参与度的中期参与度的预测。
Mobile health apps provide a unique means of collecting data that can be used to deliver adaptive interventions.The predicted outcomes considerably influence the selection of such interventions. Recourse via counterfactuals provides tangible mechanisms to modify user predictions. By identifying plausible actions that increase the likelihood of a desired prediction, stakeholders are afforded agency over their predictions. Furthermore, recourse mechanisms enable counterfactual reasoning that can help provide insights into candidates for causal interventional features. We demonstrate the feasibility of GAN-generated recourse for mobile health applications on ensemble-survival-analysis-based prediction of medium-term engagement in the Safe Delivery App, a digital training tool for skilled birth attendants.
