Improving the accessibility and relevance of Medical Nutritional Therapy among people with Type 2 diabetes in the Latino community through a customizable, AI-powered application.

项目总结 医学营养疗法(MNT)是管理2型糖尿病(T2D)的有效疗法，但研究 已经表明，很少有T2D患者坚持或接触到它。这种低利用率可以归因于 注册营养师(RDN)数量与T2D患者数量的比较，有限 MNT的报销途径，以及患者群体中的资源限制。这些问题是 由于获得护理的机会有限、经济差距和资源稀少，拉美裔社区的情况更加严重 为文化身份量身定做。目前，将文化相关性纳入MNT计划必须手动完成 通过RDN。现有的数字应用侧重于膳食跟踪或离散的生物因素(例如肠道 微生物组)，补充健康的生活方式，而不是支持MNT的交付，未能解决 个人和文化因素在饮食计划的制定和遵守中的作用。 YumAI是一款新的基于AI的应用程序，它提供并跟踪对符合MNT标准的食谱的遵守情况 根据预算、家庭、地点、季节、食物偏好和准备复杂性等因素进行定制。 通过自动调整膳食计划，YumAI通过以下方式将定制的高质量MNT直接带给患者 台式计算机和个人设备上提供的易于使用的数字应用程序。 在这个第一阶段的SBIR项目中，我们将进一步开发这个人工智能支持的应用程序，纳入来自 初步测试，确保符合ADA饮食指南和MNT规定，并优化 软件专门为个人与T2D的墨西哥体面。我们将进行两个设计思维 举办研讨会，以确定产品特性并发现配方定制和MNT合规性中的因素。 通过迭代设计过程，我们将开发YumAI的概念证明并演示算法 支持基本配方计划定制的功能。我们的两步方法平衡了合规性和 MNT标准和内置的相关因素，以定制用户需求的食谱推荐。 认识到定制计划的复杂性和遵守的可能方面的数目， 研究的目的是论证未来可以增强的解决方案的技术可行性 发展，并找出数据收集方面的差距。 该项目的成功完成将产生首个数字健康产品--YumAI的功能原型 通过T2D增加墨西哥人口获得MNT的机制。这个项目将提供证据 为未来的研究提供概念和可行性，以便为更广泛的人群扩展YumAI。它会让我们准备好迎接 第二阶段项目，探索与产品的现场交互作用和产品在解决以下问题中的有效性 以及患者忠诚度、文化意识和RDN可扩展性。

PROJECT SUMMARY Medical Nutrition Therapy (MNT) is an effective treatment for managing Type 2 diabetes (T2D), but studies have shown that few T2D patients adhere to or access it. This low utilization rate can be attributed to the small number of registered dietitian nutritionists (RDNs) compared to the number of patients with T2D, limited reimbursement pathways for MNT, and resource constraints in the patient population. These issues are exacerbated in the Latino community due to limited access to care, economic disparities, and few resources tailored to culture identity. Currently, incorporating cultural relevance into an MNT plan must be done manually by an RDN. Existing digital applications focus on meal tracking or discrete biological factors (e.g. gut microbiome), supplementing healthy lifestyles rather than supporting MNT delivery and failing to address personal and cultural factors in meal plan creation and adherence. YumAI is a novel AI-based application that delivers and tracks adherence to MNT-compliant recipes that are customized to factors such as budget, family, location, season, food preferences, and preparation complexity. By automating meal plan adjustment, YumAI brings customized, high-quality MNT directly to patients through an easy-to-use digital application available on desktop computers and personal devices. In this Phase I SBIR project, we will further develop this AI-powered application, incorporating feedback from preliminary testing, ensuring compliance with ADA dietary guidelines and MNT stipulations, and optimizing the software specifically for individuals with T2D of Mexican decent. We will conduct two design thinking workshops to identify product features and discover factors in recipe customization and MNT compliance. Through an iterative design process, we will develop a proof of concept of YumAI and demonstrate algorithmic capabilities that enable basic recipe plan customization. Our two-step approach balances compliance with MNT standards and builds in relevant factors to customize recipe recommendations to user needs. Recognizing the complexity of plan customization and the number of possible dimensions of adherence, the purpose of the research is to demonstrate technical feasibility of a solution that can be enhanced in future development and to identify gaps in data collection. Successful completion of this project will result in a functional prototype of YumAI, the first digital health mechanism for increasing access to MNT for the Mexican population with T2D. This project will provide proof of concept and feasibility for future studies to scale YumAI for a broader population. It will prepare us for a Phase II project that explores in situ interaction with the product and efficacy of the product in solving issues of and patient adherence, cultural awareness, and RDN scalability.