会议介绍:生物计算中的数字健康技术数据:扩大访问的研究努力和考虑 (PSB2024)
Michelle Holko1, Chris Lunt, Jessilyn Dunn
1International Computer Science Institute at Berkeley, Bethesda, MD 20817, USA, michelle.holko@gmail.com.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|December 31, 2023
概括
像可穿戴设备这样的数字健康技术 (DHT) 可以产生有价值的生物医学数据. 扩大对这些数据的获取,特别是来自私营部门的获取,可以促进研究和改善患者护理.
科学领域:
- 生物医学研究的研究.
- 数字健康技术数字健康技术
- 可穿戴式传感器
背景情况:
- 数字健康技术 (DHT) 和可穿戴传感器正在迅速发展,私营部门的投资很大.
- 学术机构越来越多地与科技公司合作,利用DHT进行临床研究.
- 大多数可穿戴传感器数据由私营公司持有,限制了学术研究的访问.
研究的目的:
- 探索利用DHT和可穿戴传感器数据的研究.
- 突出DHT数据的新分析方法.
- 在数字健康研究中解决多样性,公平性和包容性 (DEI).
主要方法:
- 要求的研究结果和使用DHT和可穿戴传感器数据的研究.
- 鼓励提交关于数字健康研究中新型分析方法和DEI的意见.
- 专注于通过传感器数据扩大和民主化学术研究的机会.
主要成果:
- 在生物医学研究中,DHT和可穿戴传感器数据的使用越来越多.
- 私营部门对DHT发展的重大参与和投资.
- 私营部门的DHT数据对学术研究界的有限可用性.
- 对于具有扩展数据访问的创新分析和方法存在机会.
结论:
- 扩大对私营部门DHT数据的访问可以推动创新研究.
- 解决DEI对于数字健康研究的公平进步至关重要.
- 利用可穿戴传感器数据有可能改善患者护理,早期发现疾病和保持健康.
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