Big data analytics, a fast growing subject, has begun to play a key role in the evolution of healthcare practises and research. It has given people the ability to collect, organise, analyse, and integrate huge amounts of disparate, structured, and unstructured data generated by today’s healthcare systems. Big data analytics has lately been used to help in the delivery of care and illness research. However, some basic difficulties inherent in the big data paradigm continue to stymie adoption and research advancement in this domain. We examine some of these significant problems in this work, with an emphasis on three emerging and promising areas of medical research: image, signal, and genomics-based analytics. It is described recent research that focuses on utilising massive volumes of medical data while merging multimodal data from many sources. Potential research areas in this discipline that have the potential to have a significant influence on healthcare delivery are also considered.