PDF(Pubmed)
Abstract：
During the 5th Science, Technology, and Innovation Basic Plan, the Japanese government proposed a novel societal concept -Society 5.0- that promoted a healthcare system characterized by its capability to provide unintrusive, predictive, longitudinal care through the integration of cyber and physical space. The role of Society 5.0 in managing our quality of vision will become more important in the modern digitalized and aging society, both of which are known risk factors for developing dry eye. Dry eye is the most common ocular surface disease encountered in Japan with symptoms including increased dryness, eye discomfort, and decreased visual acuity. Owing to its complexity, implementation of P4 (predictive, preventive, personalized, participatory) medicine in managing dry eye requires a comprehensive understanding of its pathology, as well as a strategy to visualize and stratify its risk factors. Using DryEyeRhythm®, a mobile health (mHealth) smartphone software (app), we established a route to collect holistic medical big data on dry eye, such as the subjective symptoms and lifestyle data for each individual. The studies to date aided in determining the risk factors for severe dry eye, the association between major depressive disorder and dry eye exacerbation, eye drop treatment adherence, app-based stratification algorithms based on symptomology, blink detection biosensoring as a dry eye-related digital phenotype, and effectiveness of app-based dry eye diagnosis support compared to traditional methods. These results contribute to elucidating disease pathophysiology and promoting preventive and effective measures to counteract dry eye through mHealth.
摘要：
在第五科学技术,创新基本计划，日本政府提出了一个新的社会概念-社会5.0-促进了医疗保健系统的特点是其提供非侵入性的能力，预测性，通过网络和物理空间的整合进行纵向护理。在现代数字化和老龄化社会中，Society5.0在管理我们的视觉质量方面的作用将变得更加重要。这两种都是干眼症的已知危险因素。干眼症是日本最常见的眼表疾病，症状包括干燥增加，眼睛不适,视力下降。由于其复杂性,P4的实施(预测性，预防性,个性化，参与式)管理干眼症的医学需要对其病理学有全面的了解，以及可视化和分层其风险因素的策略。使用DryEyeRhythm®,移动健康(mHealth)智能手机软件(app)，我们建立了一条收集干眼症整体医疗大数据的途径，例如每个人的主观症状和生活方式数据。迄今为止的研究有助于确定严重干眼的危险因素，重度抑郁症和干眼症加重之间的关系，滴眼液治疗依从性，基于症状学的基于应用程序的分层算法，眨眼检测生物传感作为干眼相关的数字表型，与传统方法相比，基于应用程序的干眼症诊断支持的有效性。这些结果有助于阐明疾病的病理生理学，并通过mHealth促进预防和有效措施来对抗干眼症。
