AI-DRIVEN LIVER CANCER DIAGNOSIS AND TREATMENT USING CLOUD COMPUTING IN HEALTHCARE

Abstract

Liver disease is a global health problem that needs to be diagnosed early and accurately in order to receive the right treatment. In this paper, an AI-solution for liver disease diagnosis and treatment on a cloud computing platform has been suggested with high accuracy and real-time testing. patients were kept in consideration keeping in mind the data set, and ML and DL algorithms are utilized in classification. Scalability, secure data processing, and real-time processing can be ensured by cloud computing, thus enhanced efficiency in medical decision-making. According to the research, AI diagnosis of liver disease can minimize diagnosis errors and enhance patient outcomes using more efficient and accurate disease prediction. It is the first to show the coming revolution in cloud computing and artificial intelligence in medicine on which a computerized and evidence-based platform has been developed for medical decision-making. Post-preprocessing of the data and feature engineering, AI model had 96.5% accuracy, 94.8% precision, 91.2% recall, and 92.5% F1-score, which is enhanced in comparison with conventional diagnostic apparatuses. Optimization in the future will consist of handling greater amounts of data, better algorithms in AI, and integration of imaging modalities to deliver greatest clinical utility. The findings confirm the ability of AI to redesign disease diagnosis process to enable early diagnosis, optimized treatment protocols, and optimal efficiency of care in treatment of liver disease.