AI-Driven Genomic Data Analysis for Cancer Prognosis and Treatment Optimization

Abstract

Genomic data analysis plays a crucial role in precision oncology by enabling targeted therapies based on a patient's genetic profile. This study explores AI techniques, including deep learning and bioinformatics, to analyze large-scale genomic datasets for cancer prognosis and treatment recommendations. Our model identifies genetic mutations and predicts patient-specific responses to various treatments, improving clinical decision-making. The results show AI’s potential in advancing precision medicine, reducing trial-and-error treatment approaches, and improving patient survival rates.