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Making
Health Care Better

Using the advancment of AI to detect Liver Cancer by using genes to make the detection much simpler

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Our Goal

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.

Objective

Train and refine artificial intelligence algorithms to accurately detect liver cancer patterns by utilizing comprehensive genetic data from the Cancer Genome Atlas and the Lübeck University Dataset.

Improve the precision and effectiveness of liver cancer detection through the integration of machine learning techniques and a diverse array of genetic information.

Leverage sophisticated AI technologies to facilitate the early identification of liver cancer, aiming to significantly improve patient outcomes by enabling prompt and targeted treatment strategies.