Through the creative application of machine learning and artificial intelligence (AI), our initiative aims to revolutionize the early identification and detection of liver cancer. We are focused on developing AI algorithms that can precisely identify patterns indicative of liver cancer using a large dataset enriched with genetic information from multiple sources. This innovative approach enhances the accuracy of liver cancer detection while providing new insights into the genetic markers associated with cancer development. By integrating these advanced AI techniques with substantial genetic data, our project strives to drive significant advancements in oncological research, potentially leading to earlier therapeutic interventions and better patient outcomes. Essential to our methodology is the acquisition and analysis of two key datasets: the Cancer Genome Atlas (TCGA) and the Lübeck University Dataset, which together offer a detailed genetic view that could enable the detection of early symptoms with unprecedented precision.