SBIR Phase I: Improved Maternal Health with Predictive Patient Monitoring

SBIR 第一阶段：通过预测性患者监测改善孕产妇健康

• 批准号: 2111902
• 负责人: Courtney Williams
• 金额: $ 25.58万
• 依托单位: Emagine Solutions Technology
• 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: 2021-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2111902&HistoricalAwards=false
• 关键词: SBIR; Phase; Improved; Maternal; Health

The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve clinical outcomes associated with preeclampsia, a potentially life-threatening condition of pregnancy occurring in the second trimester through the postpartum period. It annually affects 1 in 20 births, or 150,000 women in the U.S.A., with disadvantaged women experiencing a 2-3x increase in mortality. In the US preeclampia triples the cost of care for pregnant women, costing an estimated $2+ B per year; globally it costs 70,000 lives annually. Currently there is no way of predicting the onset of this condition. This project proposes software to predict onset to improve clinical outcomes. This Small Business Innovation Research (SBIR) Phase I project will research and develop a predictive model with 80%+ accuracy using machine learning to detect preeclampsia in the earliest stages by gathering patient-provided clinical data to inform a novel algorithm. It can be used from earliest detection through the postpartum recovery period and can provide models and alerts to both clinicians and patients.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期项目的更广泛的影响 /商业潜力是改善与先兆子痫相关的临床结果，这是在产后妊娠期间在妊娠中期发生的潜在威胁生命的怀孕状况。它每年都会影响十分之一的分娩，或在美国15万名妇女，而处境不利的妇女的死亡率增加了2-3倍。在美国，预兆子里三倍，孕妇的护理费用估计为每年$ 2+ b；在全球范围内，每年的生命为70,000。当前无法预测这种情况的开始。 该项目建议软件预测发作以改善临床结果。这项小型企业创新研究（SBIR）I阶段项目将使用机器学习研究和开发具有80％+准确性的预测模型，通过收集患者提供的临床数据以告知新算法，从而在最早的阶段检测前启示性。它可以从最早的检测到产后恢复期使用，并可以向临床医生和患者提供模型和警报。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审查标准，认为值得通过评估值得支持。