迈向健康(意识)推荐系统

Hanna Schäfer, Santiago Hors-Fraile, Raghav Pavan Karumur, André Calero Valdez, A. Said, Helma Torkamaan, Tom Ulmer, C. Trattner
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引用次数: 110

摘要

人们越来越多地使用互联网获取有关疾病、诊断和可用治疗的信息。目前,许多在线健康门户网站已经以文章的形式提供非个性化的健康信息。然而,找到与一个人的病情相关的信息,在上下文中解释这些信息,并理解医学术语和关系,可能是具有挑战性的。推荐系统(RS)已经帮助这些系统执行精确的信息过滤。在这篇短文中,我们向前迈进了一步,并展示了RS在帮助用户找到个性化、复杂的医疗干预措施或为他们提供预防性医疗措施方面取得的进展。我们确定了RS需要解决的关键挑战,以便为医疗保健等高风险领域提供所需的决策支持。
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Towards Health (Aware) Recommender Systems
People increasingly use the Internet for obtaining information regarding diseases, diagnoses and available treatments. Currently, many online health portals already provide non-personalized health information in the form of articles. However, it can be challenging to find information relevant to one's condition, interpret this in context, and understand the medical terms and relationships. Recommender Systems (RS) already help these systems perform precise information filtering. In this short paper, we look one step ahead and show the progress made towards RS helping users find personalized, complex medical interventions or support them with preventive healthcare measures. We identify key challenges that need to be addressed for RS to offer the kind of decision support needed in high-risk domains like healthcare.
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