Application of E-Healthcare Based on Machine Learning in an Internet of Things Ecosystem

Particularly in the biology and healthcare industries, advancements in technology have made it possible to collect enormous amounts of data. The obtained data is typically of an unstructured kind and can be presented in several ways, including visually, audibly, textually, etc. Technology breakthroughs, fitness bands, sensors, smart devices, even healthcare apps all have a significant impact on the healthcare industry. These innovations have brought medical care to a new level. As a result, everyone is worried about their current health and possible outcomes. Effective evaluation of clinical records and healthcare services is thus the most crucial component of the healthcare sector. By using machine learning, judgements can be made accurately and diseases can be identified earlier. Additionally, the quick and precise diagnosis of diseases is the main goal of this effort. The ischemic stroke dataset is examined in this work to enable quicker and more accurate diagnosis. There have been several ML algorithms documented from the literature, however reliability is the main issue, especially for healthcare datasets.