Radio genomics and machine learning for personalized radiotherapy

Abstract

The merging fields of radio genomics and machine learning provide a novel approach to customized radiation therapy, utilizing cutting-edge artificial intelligence technologies in conjunction with each patient's genetic composition. This mutually beneficial partnership has great potential for precisely adjusting cancer treatment. We examine the revolutionary applications in this research study, including everything from therapeutic stratification and patient empowerment to therapy optimization and predictive modeling. Critical hurdles that arise as we navigate this new region include ethical issues, data privacy concerns, and the necessity for thorough validation. However, the ability to tailor radiation therapy to each patient's unique genetic profile presents new opportunities to improve treatment outcomes, reduce side effects, and completely change the way cancer care is provided. The overall research founded that radio genomics and machine learning shows direct link with personalized radiotherapy. To guarantee these technologies' fair and efficient integration into clinical practice, the conclusion highlights the significance of responsible deployment, cooperative research, and international collaboration.