AI-Driven-IoT (AIIoT) Decision-Making System for Hepatitis Disease Patient Healthcare Monitoring
Kutubuddin Sayyad Liyakat Kazi
Abstract
The KSK1 strategy is positioned to transform decision-making processes and create a more intelligent and efficient world as AI and IoT continue to expand. This model was specifically designed to satisfy the criteria of the task that is being suggested. These classifiers are used in the case of disease datasets during the classification process, particularly in regions like those that relate to Hepatitis diseases. Three fundamental indications are considered to assess how well the classifiers are performing. It is crucial to remember that accuracy, precision, and recall are the measurements being discussed here. Through the application of the proposed KSK1 approach, an accuracy rate ranging from 85% to 91% can be obtained for every sickness. The suggested KSK1 approach's accuracy, precision, and recall are displayed. As a result, the KSK1 method approach has 93.4% accuracy, precision of 91.2%, and recall of 91.2%.