Modern technology has made it possible to gather vast quantities of medical data. It is crucial to create a healthcare system that can find and share pertinent medical information. The extraction of understandable knowledge from data relating to medical diagnoses is one of the fundamental issues in the medical field. A wireless ad hoc network is an infrastructure-less network that helps in making a healthcare system, it is made up of a massive number of nodes that are constantly linked. The amount of data rate produced during the process in these networks is significantly reduced by the clustering method deployment. In wireless ad hoc networks, clustering is a strategy for splitting large networks containing nodes into smaller groups, with each group consisting of a master node (cluster node), normal nodes (regular node), and doorway nodes. These network nodes can communicate with one another to monitor a variety of variables and are powered by batteries. As a result, energy utilization as well as the gathering of understandable data of healthcare diagnostic data are of the highest concern. This paper looks at the classification of clustering-based techniques as well as the challenges this face.