SCC-PG: Just in Time Intervention for Patients with Chronic Heart Diseases in Arizona tribes
SCC-PG:对亚利桑那州部落慢性心脏病患者进行及时干预
基本信息
- 批准号:2213915
- 负责人:
- 金额:$ 15万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-10-01 至 2024-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Cardiovascular diseases are the leading cause of death in the United States. Cardiovascular diseases are often chronic conditions that involve several costly emergency visits or long hospitalizations for the patients. Limited access to medical facilities in rural communities can result in worse health outcomes for these patients, in particular, the American Indian (AI) patients living in remote and rural areas. A considerable number of Arizonan AIs with cardiovascular conditions may be at risk of missing the window of opportunity for effective treatment and experiencing a lower chance of survival because of living far away from medical service providers. Arizona has the third largest population of Indian Americans who live in rural, tribal and often extremely isolated areas. The cardiac patients living in these areas do not have the required timely access to care, in particular to specialty services like cardiologists. Therefore, an important challenge related to these conditions for rural patients is the ‘early detection of deterioration in symptoms’, which is critical for ‘just in time’ interventions. This planning project is a collaborative effort among the Northern Arizona University (NAU) and University of Michigan (UM) as well as community leaders in rural and tribal health to discuss the best strategies to utilize an integrated remote heart monitoring system to benefit the patients with chronic heart conditions who live in rural, remote and isolated tribal areas.This planning project offers several innovative approaches by working with the tribal AI community to begin(i) Developing a new remote heart monitoring technology to predict the deterioration of the symptoms and occurrence of critical heart conditions in patients with some common chronic cardiac conditions such as atrial fibrillation and congested heart failure. Several remote heart monitoring systems have focused on reliable detection of such events, however by the time that the device alerts the patients or their family, it is already too late to seek medical help for the patients who live in rural and remote areas. Hence, our early prediction framework can give the patients enough time to seek medical assistance. This system can also help caregivers control severe symptoms, reduce readmissions, and reduce the cost associated with care; (ii) Developing deep learning-based and Markov-based prediction methods; and (iii) Developing on-device prediction methods that can work independently of the cloud in order to service the patients with no access to broadband internet. This study can be replicated for a wide range of other diseases and medical conditions and in different geographic regions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
心血管疾病是美国人死亡的主要原因。心血管疾病通常是慢性疾病,患者需要多次昂贵的急诊或长期住院治疗。农村社区医疗设施有限可能导致这些患者的健康状况恶化,特别是生活在偏远和农村地区的美洲印第安人患者。相当多患有心血管疾病的亚利桑那州人工智能患者可能会错过有效治疗的机会窗口,并且由于远离医疗服务提供者而生存的机会较低。亚利桑那州拥有第三大印度裔美国人人口,他们居住在农村,部落和通常非常孤立的地区。生活在这些地区的心脏病患者无法及时获得所需的护理,特别是心脏病专家等专业服务。因此,与农村患者的这些状况有关的一个重要挑战是“早期发现病情恶化”,这对于“及时”干预至关重要。该规划项目是北方亚利桑那大学(NAU)和密歇根大学(UM)以及农村和部落健康社区领导人之间的合作努力,以讨论利用集成远程心脏监测系统的最佳策略,使生活在农村的慢性心脏病患者受益,偏远和孤立的部落地区。这个规划项目提供了几个创新的方法,通过与部落人工智能社区合作,开始(i)开发一种新的远程心脏监测技术,以预测患有一些常见慢性心脏病(如房颤和充血性心力衰竭)的患者的症状恶化和严重心脏病的发生。一些远程心脏监测系统专注于对此类事件的可靠检测,然而,当设备提醒患者或其家人时,对于生活在农村和偏远地区的患者来说,寻求医疗帮助已经为时已晚。因此,我们的早期预测框架可以让患者有足够的时间寻求医疗援助。该系统还可以帮助护理人员控制严重症状,减少再入院,并降低与护理相关的成本;(ii)开发基于深度学习和马尔可夫的预测方法;(iii)开发可以独立于云工作的设备上预测方法,以便为无法访问宽带互联网的患者提供服务。这项研究可以在广泛的其他疾病和医疗条件以及不同的地理区域进行复制。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
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专利数量(0)
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Fatemeh Afghah其他文献
PyroTrack: Belief-Based Deep Reinforcement Learning Path Planning for Aerial Wildfire Monitoring in Partially Observable Environments
PyroTrack:基于信念的深度强化学习路径规划,用于部分可观测环境中的空中野火监测
- DOI:
10.48550/arxiv.2403.11095 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Sahand Khoshdel;Qi Luo;Fatemeh Afghah - 通讯作者:
Fatemeh Afghah
Fatemeh Afghah的其他文献
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{{ truncateString('Fatemeh Afghah', 18)}}的其他基金
Collaborative Research:CISE-MSI:DP:CNS:Adaptive Multi-Tiered, Multi-Task Base Station Infrastructure For Communication-Denied Environments
合作研究:CISE-MSI:DP:CNS:用于通信被拒绝环境的自适应多层、多任务基站基础设施
- 批准号:
2318726 - 财政年份:2023
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
CAREER: Toward Autonomous Decision Making and Coordination in Intelligent Unmanned Aerial Vehicles' Operation in Dynamic Uncertain Remote Areas
职业:在动态不确定的偏远地区实现智能无人机操作的自主决策和协调
- 批准号:
2232048 - 财政年份:2022
- 资助金额:
$ 15万 - 项目类别:
Continuing Grant
Collaborative Research: SWIFT: LARGE: AI-Enabled Spectrum Coexistence between Active Communications and Passive Radio Services: Fundamentals, Testbed and Data
合作研究:SWIFT:大型:主动通信和无源无线电服务之间人工智能支持的频谱共存:基础知识、测试平台和数据
- 批准号:
2202972 - 财政年份:2021
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
PFI-RP: Design and Fabrication of Hardware-based Security Platform using Fabrication Variability of Ultra low Power Memories
PFI-RP:利用超低功耗存储器的制造可变性设计和制造基于硬件的安全平台
- 批准号:
2204502 - 财政年份:2021
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
SCC-PG: Just in Time Intervention for Patients with Chronic Heart Diseases in Arizona tribes
SCC-PG:对亚利桑那州部落慢性心脏病患者进行及时干预
- 批准号:
2125643 - 财政年份:2021
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
Collaborative: Smart Health in the AI and COVID Era
协作:人工智能和新冠时代的智能健康
- 批准号:
2120217 - 财政年份:2021
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
Collaborative Research: CPS: Medium: Wildland Fire Observation, Management, and Evacuation using Intelligent Collaborative Flying and Ground Systems
协作研究:CPS:中:使用智能协作飞行和地面系统进行荒地火灾观测、管理和疏散
- 批准号:
2039026 - 财政年份:2021
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
Collaborative Research: CPS: Medium: Wildland Fire Observation, Management, and Evacuation using Intelligent Collaborative Flying and Ground Systems
协作研究:CPS:中:使用智能协作飞行和地面系统进行荒地火灾观测、管理和疏散
- 批准号:
2204445 - 财政年份:2021
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
Collaborative Research: SWIFT: LARGE: AI-Enabled Spectrum Coexistence between Active Communications and Passive Radio Services: Fundamentals, Testbed and Data
合作研究:SWIFT:大型:主动通信和无源无线电服务之间人工智能支持的频谱共存:基础知识、测试平台和数据
- 批准号:
2030047 - 财政年份:2020
- 资助金额:
$ 15万 - 项目类别:
Standard Grant
CAREER: Toward Autonomous Decision Making and Coordination in Intelligent Unmanned Aerial Vehicles' Operation in Dynamic Uncertain Remote Areas
职业:在动态不确定的偏远地区实现智能无人机操作的自主决策和协调
- 批准号:
2034218 - 财政年份:2020
- 资助金额:
$ 15万 - 项目类别:
Continuing Grant
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