Radiogenomics is a new and interesting field that combines genomics and radiology. It has much potential to make precision medicine better. This chapter looks at how genetic information and X-rays can be used together to describe tumours better, predict how well treatments will work, and make medical measures more effective. Radiogenomics tries to find genetic markers that are linked to how well radiotherapy works. This will make it easier to tailor treatments by taking both genetic traits and imaging information into account. The field aims to enhance patient care, predict tumour behaviour, and assess the risk of treatment-related side effects by leveraging advanced technologies such as machine learning and artificial intelligence. This part discusses the latest approaches to treating cancer, the challenges of combining and standardising data, and the importance of conducting numerous validation studies. In the end, radiogenomics could change clinical practice by giving cancer patients more personalized, effective, and safe treatment choices. Radiogenomics is an integral part of precision medicine because it uses genetic biomarkers to describe tumours better. It is now possible to use personalised medicine to treat cancer by combining radiation with machine learning and artificial intelligence. We can achieve better cancer outcomes by focusing on the harm caused by treatments and exploring data integration strategies.