The Proactive Screening and diagnosis of mild cognitive impairment and depression in patients aged 65 and over: An Implementation Study

项目摘要 拟议的计划旨在完成Miro Health最终敲定FDA所需的工作 批准自动诊断遗忘性MCI(AMCI)，这种疾病通常会导致阿尔茨海默氏症 相关痴呆症(ADRD)、非遗忘性MCI(NAMCI)和晚年抑郁症(LLD)。这个 工作包括优化我们的数据处理流水线和数字信号处理 基于收集的数据类型的方法和我们的机器学习算法的改进 通过真实世界的环境而不是通过临床研究环境。我们的目标是 通过提供普遍可用的自助式医疗服务，改善患者结局并降低医疗成本 管理移动脑评估和诊断平台。 未来的研究参与者将从诊所和社区招募。参与者将 参与新颖的移动评估以及传统的认知和精神评估。 所得数据将用于：(1)评估MIRO用于远程评估的可用性；(2) 提高功能能力量化，为平台增加RDoC元数据标签；(3) 改进用于诊断aMCI、NAMCI、LLD和合并MCI LLD的人工智能模型。 因为晚年抑郁症通常模仿MCI，而同时发生的抑郁症可能会加速 MCI向痴呆的进展，抑郁症的识别和适当的治疗可能 解决一些明显的MCI病例，并减缓其他病例的进展。并存陈述 脑部疾病是很常见的，而且越来越多的工具可以准确和 可靠地识别复杂的合并症将改善我们对最需要帮助的患者的护理。 这项计划涉及的工作将增强Miro Health的移动研究平台。这个 在移动研究平台的元数据模式中引入RDoC元数据标签 将有助于标准化临床研究，大幅减少每个项目所需的工作人员数量 研究并支持大规模可伸缩性。能够产生精确、统一数据集的增强工具将 提高研究检查疾病病因学的能力、可解释性和概括性， 遗传风险因素和干预措施。

Project Summary The proposed program aims to complete the work needed for Miro Health to finalize FDA approval for the automated diagnosis of amnestic MCI (aMCI) which often leads to Alzheimer’s and related dementias (ADRD), non-amnestic MCI (naMCI), and late life depression (LLD). The work involves the optimization of our data processing pipeline and digital signal processing methods and the refinement of our machine learning algorithms based on data types collected via real-world settings rather than through clinical research environments. Our objective is to improve patient outcomes and reduce healthcare costs by providing a universally available, self- administered mobile brain assessment and diagnostic platform. Prospective study participants will be recruited from clinics and the community. Participants will participate in novel mobile assessments and traditional cognitive and psychiatric assessments. The resulting data will be used to: (1) Assess usability of Miro for remote assessment; (2) Improve quantification of functional abilities and add RDoC metadata labels to Platform; (3) Refine A.I. models for the diagnosis of aMCI, naMCI, LLD, and comorbid MCI+LLD. Because late-life depression often mimics MCI and co-occurring depression may hasten the progression of MCI toward dementia, the identification and proper treatment of depression may resolve some apparent cases of MCI and slow the progression of others. Comorbid presentation of brain disorders is common and the increased availability of tools that can accurately and reliably identify complex comorbidities will improve care for our neediest patients. The work involved in this program will enhance Miro Health’s Mobile Research Platform. The introduction of RDoC metadata labels into our Mobile Research Platform’s metadata schema will help standardize clinical research, dramatically reduce the number of staff needed per study, and support massive scalability. Enhancing tools that yield precise, uniform data sets will improve the power, interpretability, and generalizability of studies examining disease etiology, genetic risk factors, and interventions.