We suggest a low cost, non invasive healthcare system that measures haemoglobin levels in patients and can be used as a preliminary diagnostic test for anaemia. A combination of image processing, machine learning and deep learning techniques are employed to develop predictive models to measure haemoglobin levels. This is achieved through the color analysis of the fingernail beds, palpebral conjunctiva and tongue of the patients. This predictive model is then encapsulated in a healthcare application. This application expedites data collection and facilitates active learning of the model. It also incorporates personalized calibration of the model for each patient, assisting in the continual monitoring of the haemoglobin levels of the patient. Upon validating this framework using data, it can serve as a highly accurate preliminary diagnostic test for anaemia.

中文翻译：

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基于智能手机的多输入工作流程，可使用机器学习技术以非侵入方式估算血红蛋白水平

我们建议一种低成本，无创的医疗系统，该系统可以测量患者的血红蛋白水平，并且可以用作贫血的初步诊断测试。结合图像处理，机器学习和深度学习技术来开发预测模型以测量血红蛋白水平。这是通过对患者指甲床，睑结膜和舌头的颜色分析来实现的。然后将此预测模型封装在医疗保健应用程序中。该应用程序加快了数据收集的速度，并促进了模型的主动学习。它还结合了针对每个患者的模型的个性化校准，有助于持续监测患者的血红蛋白水平。使用数据验证此框架后，