The intersection of artificial intelligence and lung nodule research: current applications and future prospects

Lung cancer represents a primary global cause of cancer-related mortality, imposing substantial healthcare burdens on both patients and public health systems. Pulmonary nodules, as early-stage manifestations of lung cancer, exhibit considerable morphological heterogeneity. Consequently, precise identification and clinical management of these nodules are critical for effective lung cancer prevention. In recent years, artificial intelligence (AI) has emerged as a transformative component in modern oncology, providing advanced tools for end-to-end pulmonary nodule management. This review systematically analyzes existing literature through bibliometric assessment to synthesize AI applications across the pulmonary nodule care continuum. AI-powered clinical decision support systems and personalized treatment planning are reshaping precision oncology paradigms. Current research advancements and prevailing challenges are critically examined to identify potential future breakthroughs. The comprehensive synthesis presented herein aims to establish a foundational conceptual framework for researchers and clinicians, while facilitating efficient translation of AI technologies into clinical practice for pulmonary nodule diagnosis and therapy.