Analysis of Clustering Algorithms in Machine Learning for Healthcare Data

In fields such as healthcare, the use of data can lead to an increased chance of reaching patient outcomes. This research project aims to develop an effective way to analyze clustering algorithms in machine learning for healthcare data. This paper investigates four different algorithms and provides a comparison of their efficiency. Data in science and technology are expanding at an exponential rate. It is important that these changes can be analyzed properly with algorithms so that they can be used appropriately and efficiently during the analysis process, specifically when it comes to health care. Automated systems are becoming more prevalent in today’s society because they have the ability to analyze large amounts of information automatically which extends their usage throughout many industries.