Digital health-based medical technology (m-health) uses mobile phones and
other patient monitoring equipment to keep tabs on a patient's health. It is largely
acknowledged as an important modern-era technological accomplishment.
Traditionally, big data analytics and intelligent machines have been used in m-health to
provide far more productive medical coverage. Current therapeutic research utilises a
variety of data types, including electronic health records (EHRs), diagnostic images,
and professional language that appear to be disparate, unclear, and disorganised. In
addition, it makes a substantial contribution to the emergence of a large number of
unstructured and jumbled data sources as a result of mobile platforms and healthcare
infrastructure. The use of machine intelligence and big data analytics to enhance the mhealth infrastructure is thoroughly examined in this chapter. Additionally, various
machine learning big data approaches and platforms are studied to the data source,
methodology used, and application area. The overall findings of this study will
undoubtedly affect the creation of techniques for processing m-health data more easily
utilising a resource that incorporates big data and AI.
Keywords: Agent-Based technologies, m-Healthcare, Big data analytics, Deep learning, IoT.
