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.

项目摘要 医学营养疗法（MNT）是治疗2型糖尿病（T2D）的有效疗法，但研究 已经表明，很少有T2D患者坚持或访问它。这种低利用率可以归因于小 与T2D患者数量相比，注册营养师（RDN）数量有限 MNT的报销途径以及患者群体的资源限制。这些问题 在拉丁裔社区，由于获得护理的机会有限、经济差距和资源匮乏， 适合文化身份。目前，将文化相关性纳入MNT计划必须手动完成 一个RDN。现有的数字应用程序专注于膳食跟踪或离散生物因素（例如肠道 微生物组），补充健康的生活方式，而不是支持MNT的交付和未能解决 个人和文化因素在膳食计划的创建和遵守。 YumAI是一种基于人工智能的新型应用程序，可提供并跟踪遵守符合MNT的食谱， 根据预算、家庭、地点、季节、食物偏好和准备复杂性等因素定制。 通过自动调整膳食计划，Yumai通过以下方式直接为患者提供定制的高质量MNT 一个易于使用的数字应用程序，可在台式计算机和个人设备上使用。 在这个第一阶段SBIR项目中，我们将进一步开发这个人工智能驱动的应用程序，并结合来自 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考 研讨会，以确定产品功能，并发现配方定制和MNT合规性的因素。 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， MNT标准化并内置相关因素，以根据用户需求定制配方建议。 认识到计划定制的复杂性和遵守的可能维度的数量， 研究的目的是证明解决方案的技术可行性，以便在未来得到增强 在数据收集方面，我们将继续努力开发和找出差距。 该项目的成功完成将产生Yumai的功能原型， 为墨西哥T2D患者提供更多MNT服务的机制。这个项目将提供证据 未来研究将YumAI扩展到更广泛人群的概念和可行性。它将为我们准备一个 第二阶段项目，探索与产品的现场相互作用以及产品在解决以下问题方面的功效： 患者依从性、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.