SBIR Phase I: Development of novel artificial intelligence (AI)-enabled, non-invasive, heart attack diagnostics

SBIR 第一阶段：开发新型人工智能 (AI) 支持的非侵入性心脏病诊断

• 批准号: 2208248
• 负责人: Jitto Titus
• 金额: $ 25.59万
• 依托单位: RCE TECHNOLOGIES, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-15 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2208248&HistoricalAwards=false
• 关键词: SBIR; Phase; Development; novel; artificial

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is a novel, portable, diagnostic device for non-invasively diagnosing myocardial infarctions (MI) and ischemia in real-time with a high level of sensitivity and specificity. The system aims to provide an accurate point-of-care clinical classification for the 805,000 heart attack cases occurring in the US each year with a real-time diagnostic and monitoring tool. The system aims to significantly reduce the time needed with current invasive sampling and blood analysis measures, thereby improving patient outcomes during the first critical hours of an MI while saving healthcare resources and improving efficiency. The portable nature of the technology enables other forms of integration including at home, in clinic, hospital bedside use, or field use applications.This Small Business Innovation Research (SBIR) Phase I project will develop a proof-of-concept diagnostic-prognostic machine learning-based system for detecting MI. The scope of activities includes testing multiple techniques and models and producing distribution analyses and event plots of training data in order to optimize performance compared to clinically adjudicated events. Success measures include a data model which, when using their proprietary external noninvasive transdermal biomarker sensor with their wearable garment electrocardiograms (EKGs), are able to detect MI with 85% accuracy. The device will also be able to detect clinically relevant ischemia with 85% accuracy. These results will progress the company’s objective of completing a standalone, noninvasive, real-time diagnostic and remote monitoring tool.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.

这项小型企业创新研究（SBIR）I期项目的更广泛影响是一种新颖的，便携式的，可用于非侵入性诊断性心肌违规（MI）和缺血的诊断装置，具有较高的敏感性和特异性。该系统旨在通过实时诊断和监测工具为805,000个心脏病发作病例提供准确的护理临床分类。该系统旨在通过当前的侵入性抽样和血液分析措施大大减少所需的时间，从而在MI的第一个关键小时内改善患者的预后，同时节省医疗资源并提高效率。该技术的便携性可以使其他形式的集成形式，包括在家中，在诊所，医院的床边使用或现场使用应用中。此小型企业创新研究（SBIR）I阶段项目将开发一种基于诊断诊断的基于诊断的基于诊断的机器学习系统，用于检测MI。活动的范围包括测试多种技术和模型，以及与临床调整事件相比，为了优化培训数据的分布分析和事件图，以优化性能。成功措施包括一个数据模型，当使用其专有的外部非侵入性透皮生物标志物传感器时，其可穿戴服装心电图（EKG）能够以85％的精度检测MI。该设备还将能够以85％的精度检测临床相关的缺血。这些结果将促进公司的目标，即完成独立的，无创的，实时诊断和远程监控工具。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响评估审查标准，认为通过评估被认为是珍贵的支持。