在乳腺癌幸存者的内分泌疗法坚持的多式传感和建模
Fangxu Yuan1, Navreet Kaur1, Zhiyuan Wang1
1Department of Systems and Information Engineering, University of Virginia, USA.
概括
预测乳腺癌内分泌治疗的坚持是复杂的. 多式传感,整合可穿戴设备,药物和调查数据,有望改善坚持预测和个性化干预措施.
科学领域:
- 在瘤学瘤学.
- 数字健康数字健康
- 行为科学 行为科学
背景情况:
- 内分泌疗法对于预防乳腺癌复发至关重要,但由于多方面的因素,坚持是具有挑战性的.
- 现有的移动传感粘附预测模型往往缺乏时间细粒度和多式联络整合,限制了它们的有效性.
- 了解短期和长期的行为变化是制定定制的坚持干预措施的关键.
研究的目的:
- 开发和评估一种多式传感框架,用于预测乳腺癌幸存者每日内分泌治疗的坚持.
- 调查来自各种数据模式的临时适应性输入对坚持预测准确性的影响.
- 探索行为,生理,心理和环境数据的不同时间窗口如何影响坚持预测.
主要方法:
- 招募了20名乳腺癌幸存者进行纵向研究.
- 收集的多式联络数据:可穿戴产生的生理特征 (Fitbit),药物事件监测系统 (MEMS) 和生态瞬间评估 (EMA).
- 在不同的时间窗口中使用多式联运数据进行临时适应建模,以预测第二天的坚持.
主要成果:
- 多模式传感数据显示,可预测每日内分泌疗法遵守的可行性,准确度中等.
- 综合多式模式在坚持预测方面始终优于单式模式模型.
- 每种数据模式的预测能力都取决于时间的接近,这突显了模拟即时和长期模式的重要性.
结论:
- 多模式传感提供了一种可行的方法来预测乳腺癌幸存者的每日内分泌治疗坚持.
- 与单一模式相比,整合多样化,适应时间的数据流显著提高了预测准确性.
- 个性化,暂时适应的数据融合策略对于推进坚持监测和改善乳腺癌患者的干预设计至关重要.
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