This chapter examines the essential role of early cancer detection in reducing mortality rates amidst the rising global burden of the disease. According to the World Health Organization (WHO), cancer claimed 10 million lives in 2020, underscoring its position as a leading cause of death worldwide. In India, data from the National Cancer Registry Program (ICMR) revealed a concerning increase in cancer cases, growing from 1.3 million in 2020 to 1.4 million in 2022, accompanied by a corresponding rise in mortality rates. Traditional diagnostic tools, such as Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and Computerized Tomography (CT), depend on expert interpretation, which is often time-consuming and prone to human error, potentially delaying diagnosis. To address these challenges, this chapter explores the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing cancer detection through automated imaging analysis. Leveraging advancements in AI-ML, innovative techniques and models have emerged, allowing for faster, more accurate image analysis and reducing reliance on manual review. The chapter provides an in-depth analysis of the most impactful AI-ML techniques, emphasizing their ability to improve diagnostic accuracy and efficiency. Additionally, a comprehensive literature review offers insights into how Machine Learning and Deep Learning (DL) are revolutionizing cancer diagnostics, enabling more reliable, swift, and precise detection methods.