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Neural Prediction of Patient Needs in an Ovarian Cancer Online Discussion Forum

机译:卵巢癌网上讨论论坛中患者需求的神经预测

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Social media is an important source to learn the concerns and needs of patients and caregivers in home care settings. However, manually identifying their needs can be labor-intensive and time-consuming. In this paper, we address the problem of need detection, automatically identifying patient needs in text. We explore both neural and traditional machine learning approaches, and evaluate them on a newly annotated dataset in an ovarian cancer discussion forum. We discuss issues and challenges of this novel task.
机译:社交媒体是学习家庭护理环境中患者和护理人员的担忧和需求的重要来源。但是,手动识别他们的需求可以是劳动密集型和耗时的。在本文中,我们解决了需要检测的问题,自动识别文本中的患者需求。我们探索神经和传统的机器学习方法,并在卵巢癌讨论论坛中评估新注释的数据集。我们讨论了这项新任务的问题和挑战。

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