  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.
