Recently, genetic analysis powered by deep learning has proven to be a powerful tool in medicine, particularly in the development of targeted therapies for complex diseases such as cancer. By enabling a more precise and in-depth interpretation of genetic data, artificial intelligence can uncover patterns and mutations that may go undetected using traditional methods.<br /><br />Deep learning, a branch of artificial intelligence, can process vast amounts of genetic information to identify mutations and variations that contribute to disease progression. For example, this technology can be applied to understand the impact of specific genetic mutations in breast or colon cancer, leading to the development of more effective treatments that directly target those mutations.<br /><br />Furthermore, deep learning-based genetic analysis allows for the identification of patients who are more likely to respond to certain therapies, enabling physicians to tailor treatment plans accordingly. These targeted therapies are not only more effective but also safer, as the drugs are designed to interact only with diseased cells while sparing healthy tissue.<br /><br />Despite these advantages, challenges remain—particularly in terms of the high costs and limited availability of genetic analysis technologies, as well as the ongoing need to update genomic databases to ensure accurate diagnosis and treatment.<br /><br />Integrating deep learning with genetic analysis marks a significant step toward more precise, personalized medicine that places the individual patient’s needs at the center of therapeutic strategies.<br /><br />University of Al-Mustaqbal The First University in Iraq.<br /><br />