比色法和电化学筛选用于糖尿病和糖尿病视网膜病变的早期检测-传感器阵列和机器学习的应用。
Colorimetric and Electrochemical Screening for Early Detection of Diabetes Mellitus and Diabetic Retinopathy-Application of Sensor Arrays and Machine Learning.
机构信息
Center for Eye Research, Department of Ophthalmology, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Kirkeveien 166, 0450 Oslo, Norway.
Department of Medical Biochemistry, Institute of Clinical Medicine, University of Oslo, 0424 Oslo, Norway.
出版信息
Sensors (Basel). 2022 Jan 18;22(3):718. doi: 10.3390/s22030718.
In this review, a selection of works on the sensing of biomarkers related to diabetes mellitus (DM) and diabetic retinopathy (DR) are presented, with the scope of helping and encouraging researchers to design sensor-array machine-learning (ML)-supported devices for robust, fast, and cost-effective early detection of these devastating diseases. First, we highlight the social relevance of developing systematic screening programs for such diseases and how sensor-arrays and ML approaches could ease their early diagnosis. Then, we present diverse works related to the colorimetric and electrochemical sensing of biomarkers related to DM and DR with non-invasive sampling (e.g., urine, saliva, breath, tears, and sweat samples), with a special mention to some already-existing sensor arrays and ML approaches. We finally highlight the great potential of the latter approaches for the fast and reliable early diagnosis of DM and DR.
在这篇综述中，我们选择了一些与糖尿病（DM）和糖尿病视网膜病变（DR）相关的生物标志物传感研究工作，旨在帮助和鼓励研究人员设计基于传感器阵列和机器学习（ML）的设备，以便对这些破坏性疾病进行快速、准确且经济高效的早期检测。首先，我们强调了为这些疾病开发系统性筛查方案的社会意义，以及传感器阵列和 ML 方法如何有助于早期诊断。然后，我们介绍了与 DM 和 DR 相关的生物标志物的比色和电化学生物传感研究工作，这些研究工作涉及非侵入性采样（例如尿液、唾液、呼吸、眼泪和汗液样本），特别提到了一些现有的传感器阵列和 ML 方法。最后，我们强调了这些方法在 DM 和 DR 的快速、可靠早期诊断方面的巨大潜力。
Zotero 插件