AI-Driven IoT based Decision Making for Hepatitis Diseases Patient’s Healthcare Monitoring: KSK Approach for Hepatitis Patient Monitoring
Kazi Kutubuddin Sayyad Liyakat, Suhas B Khadake, Pravin S More, Renuka J Shinde, Komal P Kondubhairi, Shashikant S Kamble
Abstract
Making decisions is a crucial part of the medical treatment of hepatitis patients. The KSK technique transforms decision-making by fusing the power of artificial intelligence (AI) with the internet of things (IoT). It improves data accuracy and reliability, enables real-time decision-making, and increases the solution's cost-effectiveness. However, businesses must address the issues associated with its use if they are to fully realise the potential of this approach. The KSK strategy has the potential to transform decision-making procedures and create a more intelligent and efficient world as AI and IoT continue to expand. This particular model was created specifically to meet the demands of the task that is being offered. These classifiers are applied to disease datasets during the classification process, particularly those related to hepatitis conditions. Three fundamental indicators are taken into account when assessing how well the classifiers are performing. Note that the metrics of accuracy, precision, and recall are being discussed here. The proposed KSK approach can be used to obtain an accuracy rate ranging from at least 85% to as much as 91% for all illnesses. The suggested KSK approach's accuracy, precision, and recall are displayed. As a result, the KSK method has 91.3% accuracy, 90.1% precision, and 90.6% recall.