Lung cancer stands as a serious health challenge, prompting the exploration of innovative detection methods. Volatile organic compounds (VOCs) found in exhaled breath air are becoming a relevant opportunity for early cancer detection, including lung cancer, without invasive procedures or high costs. Unlike traditional approaches, which target specific compounds, this study analyzes overall compositional profiles, maximizing detection efficiency. The results highlight the potential of AI-driven techniques in revolutionizing early cancer detection for clinical use.