Existing patient data analytics platforms fail to incorporate information that has context, is personal, and topical to patients. For a recommendation system to give a suitable response to a query or to derive meaningful insights from patient data, it should consider personal information about the patient's health history, including but not limited to their preferences, locations, and life choices that are currently applicable to them. In this review paper, we critique existing literature in this space and also discuss the various research challenges that come with designing, building, and operationalizing a personal health knowledge graph (PHKG) for patients.
On Curating Responsible and Representative Healthcare Video Recommendations for Patient Education and Health Literacy: An Augmented Intelligence Approach
研究表明，三分之一的美国成年人使用互联网来诊断或了解健康问题。然而，在线获取保健信息可能会加剧保健信息提供和使用方面的差距。健康信息寻求行为（Health Information Seeking Behavior，HISB）是指个体寻求有关其健康、风险、疾病和健康保护行为的信息的方式。对于在数字媒体平台上搜索健康信息的患者来说，健康素养的鸿沟可能会因为他们自己缺乏知识和算法建议而加剧，结果会对弱势群体，少数民族和低健康素养用户产生不成比例的影响。这项研究报告了对上述挑战的探索性调查，通过研究是否可以使用先进的分析方法生成负责任和有代表性的建议，这些方法适用于YouTube社交媒体平台上的慢性疾病（糖尿病）的大型视频及其元数据。该文件的重点是与使用糖尿病视频的演员的人口特征相关的偏见，这些视频是根据多个标准检索和策划的，例如编码的医疗内容及其可理解性，以满足患者教育和人口健康素养需求。这种方法通过将卫生专业人员和患者的观点结合到一个可扩展和可推广的机器学习框架中，为患者赋权和改善健康结果，为人类在环，增强智能，偏见意识和负责任的算法建议的创新提供了巨大的机会。
Leveraging Large Language Models for Patient Engagement: The Power of Conversational AI in Digital Health
IBM T. J. Watson Research Center（IBM TJ沃森研究中心）；Morehouse School of Medicine（莫尔豪斯医学院）；Cleveland Clinic Foundation（克利夫兰诊所基金会）；Queen’s University（女王大学）；Red Hat（红帽公司）
Patients With Personality: Realistic Patient Simulation through Controlled Diversity and Selective Disclosure
Technical University of Munich（慕尼黑技术大学）；Munich Center for Machine Learning（慕尼黑机器学习中心）；TUM University Hospital（慕尼黑技术大学医院）；Google DeepMind（谷歌DeepMind）；Google Research（谷歌研究）；Imperial College London（伦敦帝国学院）
Personalized Digital Health Modeling with Adaptive Support Users
Department of Computer Science, University of California, Irvine（加州大学尔湾分校计算机科学系）；Thrive AI Health；Sue & Bill Gross School of Nursing , University of California, Irvine（加州大学尔湾分校苏和比尔·格罗斯护理学院）
'A net for everyone': fully personalized and unsupervised neural networks trained with longitudinal data from a single patient
German Cancer Research Center (DKFZ)（德国癌症研究中心）；Heidelberg University（海德堡大学）；University Hospital Essen (AöR)（埃森大学医院）；University Medicine Essen（埃森大学医学院）；German Cancer Consortium (DKTK)（德国癌症联盟）
University of Southern Queensland（南昆士兰大学）；Royal Brisbane and Women’s Hospital（皇家布里斯班妇女医院）；Queensland University of Technology（昆士兰科技大学）；Lingnan University（岭南大学）
