Medical science has witnessed significant progress with the integration of deep learning techniques into genetic analysis, making these smart tools highly effective in designing targeted therapies for complex diseases, particularly cancer. By enabling a more in-depth and accurate analysis of genetic data, artificial intelligence can detect patterns and mutations that are often undetectable using traditional methods.<br /><br />Deep learning, a branch of artificial intelligence, processes vast amounts of biological data to identify genetic variations that contribute to disease development. For instance, it can be used to analyze mutations associated with breast or colon cancer, paving the way for more precise therapies that directly target these specific mutations, resulting in more effective treatment outcomes.<br /><br />This approach also helps physicians identify patients who are more likely to respond to certain treatments, thereby enhancing the success of personalized therapeutic strategies. Because these treatments are designed to interact only with the affected cells, they are not only more effective but also safer, reducing the risk of harm to healthy tissues.<br /><br />Despite its promising potential, this technology still faces challenges, including high costs, limited accessibility to genetic analysis tools, and the ongoing need to update genetic databases to ensure accurate diagnoses and effective treatments.<br /><br />Al-Mustaqbal University The first University in Iraq.<br />