SBIR Phase I: Hair Genome Project - Computational approach to classifying hair profiles and dermatological health disparities in underserved communities

这个小企业创新研究（SBIR）第一阶段项目的广泛影响/商业潜力将是一个包容性的平台，为个人提供数据驱动的、个性化的头发健康见解。头发健康在整体心理/身体健康中起着很大的作用；然而，由于缺乏透明的数据，在获取优质产品和护理信息方面处于不成比例的不利地位，少数民族社区尤其如此。这种差异导致个人使用的产品和/或穿的风格对头发和头皮健康有不利影响。拟议中的技术将弥补这些差距，为用户提供头发/头皮健康的见解，并根据他们的头发特征和目标为他们匹配合适的产品和方案。与此同时，可以利用该平台的数据和用户参与度，为品牌、医疗保健提供商、保险公司等提供更深入的见解，了解客户的头发护理相关目标、痛点和健康状况。除了支持头发健康外，该项目还将减轻因不合适的产品和护理方法而引起的头皮和头发病变（如脱发、烧伤、破损、接触性皮炎）。这个小企业创新研究（SBIR）第一阶段项目旨在开发一个数据驱动的头发智能平台，利用大数据使所有人的头发洞察民主化。该技术和平台将利用来自同行评审出版物和科学支持数据库以及用户本身的大数据，不断完善个性化见解，并根据他们独特的头发特征了解客户需求。使用专有算法，该技术将能够无缝识别和绘制不同的头发类型，识别次要独特因素（孔隙度、密度、质地等），绘制和分析产品中的不同成分，跟踪和绘制不同的治疗方案和产品使用情况，并开发情感分析、模式和预测。本项目将：1)开发高置信度头发轮廓分类的训练数据集和分层算法；2)通过与皮肤科住院医师的对比研究，验证并完善毛发特征分类系统；3)建立概念验证，展示准确的头发特征分类和数据驱动的产品/风格推荐之间的联系，以提高对头发的尊重。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be an inclusive platform offering individuals access to data-driven, personalized insights on hair health. Hair health plays a large factor in overall mental/physical health; however, an absence of transparent data has disproportionately disadvantaged access to quality products and care information, particularly among minority communities. This disparity has led individuals to use products and/or wear styles that adversely impact hair and scalp health. The proposed technology will bridge these gaps, providing users with hair/scalp health insights and matching them with suitable products and regimens for their hair profile and goals. At the same time, the data and user engagement with the platform can be leveraged to offer brands, healthcare providers, insurance companies, etc. with deeper insights into their customers’ hair care-related goals, pain points, and health conditions. In addition to supporting hair health, this project will mitigate the scalp and hair pathologies (e.g., alopecia, burns, breakage, contact dermatitis) stemming from ill-suited products and care practices.This Small Business Innovation Research (SBIR) Phase I project aims to develop a data-driven hair intelligence platform that uses big data to democratize hair insights for all. The technology and platform will leverage big data from peer-reviewed publications and science-backed databases as well as the users themselves, to continually refine personalized insights and understand customer needs in the context of their unique hair profile. Using proprietary algorithms, the technology will be able to seamlessly recognize and map different hair types, identify secondary unique factors (porosity, density, texture, etc.), map and analyze different ingredients in products, track and map different treatment regimens and product usage, and develop sentiment analysis, patterns, and predictions. This project will: 1) Develop training dataset and tiered algorithm for hair profile classification with high confidence; 2) Validate and refine the hair profile classification system through a comparative study with dermatology residents; and 3) Establish proof-of-concept demonstrating the connection between accurate hair profile classification and data-driven product/style recommendations to improve hair-esteem.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.