AI-Driven-IoT(AIIoT)-Based Decision Making in Kidney Diseases Patient Healthcare Monitoring
Kutubuddin Sayyad Liyakat Kazi
Abstract
As artificial intelligence (AI) and the internet of things (IoT) continue to grow, the KSK approach is poised to revolutionize decision-making processes and make the world a more intelligent and efficient place. To fulfill the requirements of the task that is being proposed, this model was developed expressly for that purpose. During the classification process, these classifiers are utilized in the case of disease datasets, specifically in areas such as those that belong to kidney diseases. When it comes to determining how effectively the classifiers are functioning, there are three basic indicators that are taken into consideration. It is important to note that this is referring to the metrics of accuracy, precision, and recall. It is possible to acquire an accuracy rate that ranges from a minimum of 87% to a maximum of 92.5% for each and every illness by utilizing the proposed KSK approach.