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首页> 外文期刊>Biomedical and Health Informatics, IEEE Journal of >A DNA-Based Intelligent Expert System for Personalised Skin-Health Recommendations
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A DNA-Based Intelligent Expert System for Personalised Skin-Health Recommendations

机译:基于DNA的智能专家系统,用于个性化皮肤健康建议

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摘要

Intensive attention on personalised skin-health solutions is on account of incomparable love of skin and an urgent need for effective treatment. In the meanwhile, people have great expectations on how to utilise genetic knowledge of our body to provide a precise solution for different individuals, such as daily use of skin-health products, since the rapid development of genetic test services and skin-health science. However, the complexity of multi-modal data, the establishment of correlations between consumer genetic data and product ingredients are the main obstacles encountered today. Determining to settle such obstacles, a personalised recommendation expert system for selecting optimised skin-health product within the category based upon genetic phenotypes for each consumer was introduced in this article. Random Forests were implemented to achieve automatic product categorisation, the performance discussed and compared with SVM and Logistic Regression. Lastly, categorised skin-health product suggestion was made with an optimised recommendation model based on associated genetic phenotype information. Potential changes (up to 71.0% more phenotypic relevant ingredients) from experiments using real product data were demonstrated and compared with imitated cases of real-life human selections.
机译:关于个性化皮肤解决方案的强化关注是由于对皮肤无与伦比的热爱和迫切需要有效治疗的迫切需要。与此同时,人们对如何利用对我们身体的遗传知识提供了巨大的期望,以便为不同个体提供精确的解决方案,例如日常使用皮肤保健品,因为遗传测试服务和皮肤健康科学的快速发展。然而,多模态数据的复杂性,消费者遗传数据和产品成分之间的相关性是今天遇到的主要障碍。在本文中介绍了在本文中引入了基于每个消费者的遗传表型选择类别的个性化推荐专家系统的个性化推荐专家系统。随机森林实施以实现自动产品分类,讨论的性能和与SVM和Logistic回归相比。最后,基于相关的遗传表型信息,用优化的推荐模型进行分类的皮肤健康产品建议。使用真实产品数据的实验潜在变化(高达71.0%的表型相关成分),并与实际人类选择的模仿病例进行了比较。

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