Precision oncology, a burgeoning field situated at the confluence of medicine, genomics, and computational intelligence, is poised to redefine cancer detection and treatment paradigms. This book chapter explores the transformative role of computational intelligence in advancing precision oncology, focusing on machine learning, deep learning, and other computational techniques applied to cancer detection. We begin by outlining the limitations of traditional cancer detection methods and how computational approaches offer new possibilities for early diagnosis and personalized treatment strategies. Genomics and bioinformatics are highlighted for their crucial role in analyzing vast biological datasets to identify cancer biomarkers and predict disease progression. Advancements in imaging technologies and the integration of artificial intelligence (AI) to interpret radiological images are discussed for their impact on tumor detection and characterization. Additionally, we explore digital pathology and its contribution to cancer diagnosis through automated analysis of tissue samples. Ethical considerations and challenges associated with implementing computational intelligence in clinical settings are addressed, emphasizing data privacy, algorithm transparency, and equitable access to technology-driven healthcare solutions. In summary, this book chapter provides a concise overview of how computational intelligence is revolutionizing precision oncology. By leveraging cutting-edge technologies, we aim to enhance cancer detection accuracy and develop personalized treatment plans that improve patient outcomes. The potential of computational methods to decipher complex biological data and optimize clinical decision-making underscores a promising future for precision oncology.