The Role of Large-Scale Data Infrastructure in Developing Next-Generation Deep Brain Stimulation Therapies.

The Role of Large-Scale Data Infrastructure in Developing Next-Generation Deep Brain Stimulation Therapies.
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大规模数据基础设施在开发下一代深部脑刺激疗法中的作用。

DOI:
10.3389/fnhum.2021.717401
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发表时间:
2021
影响因子:
2.9
通讯作者:
Pepin B
Pepin B
中科院分区:
医学3区
文献类型:
--
作者:
Chen W;Kirkby L;Kotzev M;Song P;Gilron R;Pepin B

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神经调节技术的进步有望利用个性化的刺激模式来治疗患者独特的大脑网络病理。为了实现这些目标,使用传感设备的神经调节临床试验通常会生成大型多模式数据集。然而,随着数据采集的扩展,存储、管理和分析相关数据集也变得越来越困难,这些数据集将复杂的神经和可穿戴时间序列数据与患者症状状态的动态评估相结合。在这里,我们讨论一个可扩展的基于云的数据平台,该平台可以实现多模式神经技术数据集的摄取、聚合、存储、查询和分析。这种大规模数据基础设施将加速转化神经调节研究,并促进下一代深部脑刺激疗法的开发和交付。
Advances in neuromodulation technologies hold the promise of treating a patient’s unique brain network pathology using personalized stimulation patterns. In service of these goals, neuromodulation clinical trials using sensing-enabled devices are routinely generating large multi-modal datasets. However, with the expansion of data acquisition also comes an increasing difficulty to store, manage, and analyze the associated datasets, which integrate complex neural and wearable time-series data with dynamic assessments of patients’ symptomatic state. Here, we discuss a scalable cloud-based data platform that enables ingestion, aggregation, storage, query, and analysis of multi-modal neurotechnology datasets. This large-scale data infrastructure will accelerate translational neuromodulation research and enable the development and delivery of next-generation deep brain stimulation therapies.
DOI: 10.1007/s11548-015-1189-y
发表时间: 2015-06
影响因子: 3
作者:
D'Haese, Pierre-Francois;Konrad, Peter E.;Pallavaram, Srivatsan;Li, Rui;Prassad, Priyanka;Rodriguez, William;Dawant, Benoit M.
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