A Multilayered Framework for Analysis and Prediction of Haemophilia Using Machine Learning Techniques Based E-Health System

Abstract

Technology and information-based e-Health systems are essential to the delivery of healthcare; these include teaching and learning programs as well as remote consultation services that have been widely implemented to support many medical specialities and their corresponding remote patient populations. Because of this, e-Health systems are being utilised more and more as a passive as well as an active technique to address issues (such staffing shortages, lack of resources, and lack of knowledge) in the healthcare sector and have been shown to significantly enhance the general health of many nations. While numerous e-Health systems have been created and employed to carry out diverse functions in the medical field, including remote consultation, hospital administration, electronic health record administration, and health awareness, a dearth of research has been found concerning the analysis and prediction of haemophilia in the context of e-Health systems. Because of this, a multilayered framework for the investigation and prediction of haemophilia using machine learning techniques was developed in response to the observation.