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CURATE.AI COR-Tx平台作为脑瘤后放射治疗治疗患者的认知功能数字治疗和数字诊断:未来混合方法可行性临床试验的协议
Alexandria Remus1,2,3,4, Xavier Tadeo2,3, Grady Ng Shi Kai3,5
1Heat Resilence and Performance Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
BMJ open
|October 25, 2023
概括
这项研究介绍了CURATE.AI COR-Tx,这是一个针对正在接受放射治疗的大脑瘤患者的个性化AI平台. 它将人工智能驱动的剂量与数字认知训练相结合,以改善认知功能,旨在实现更有效,更个性化的干预.
科学领域:
- 神经科学是一个神经科学.
- 人工智能的人工智能
- 数字健康数字健康
背景情况:
- 对于脑瘤患者的传统放射治疗干预通常由于固定的治疗参数而产生不理想的结果.
- 个性化干预对于解决癌症治疗期间患者状态的动态变化至关重要.
- 现有的认知康复疗法可能无法随着时间的推移充分适应个体患者的需求.
研究的目的:
- 评估CURATE.AI COR-Tx平台作为认知功能数字干预和诊断工具的可行性.
- 评估个性化,人工智能驱动的认知培训计划的可接受性,可用性和实用性.
- 在接受放射治疗的脑瘤患者中探索定制数字认知训练的潜在有效性.
主要方法:
- 一个前性的,单中心,单臂,混合方法可行性试验.
- 招募15名接受放射治疗的脑瘤患者.
- 使用CURATE.AI COR-Tx平台进行为期10周的远程家庭个性化数字干预,在多个时间点进行认知评估.
主要成果:
- 评估了可行性结果,包括可接受性,需求,实施,实用性和可用性.
- 用户体验通过患者访谈和研究小组焦点小组来评估.
- 对所有收集的数据进行了定量和定性分析.
结论:
- CURATE.AI COR-Tx平台为脑瘤患者提供了新的,个性化的认知支持方法.
- 这种人工智能驱动的数字干预的可行性需要在更大的临床试验中进一步调查.
- 个性化数字认知训练有望改善瘤病人的认知功能.
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