Inteligencia artificial en el abordaje clínico del cáncer de pulmón en el continuum asistencial: revisión crítica

Objective: to analyze the impact of artificial intelligence on the comprehensive management of lung cancer, assessing its diagnostic, therapeutic, and prognostic applications, as well as the barriers to its clinical implementation during the period 2021–2025. Methods: A narrative review was conducted of studies applying algorithms to personalized prevention, automated screening, precision diagnosis, and individualized prognostic stratification. Results: Potential benefits identified include greater sensitivity for early detection and optimization of therapeutic decision-making, along with limitations such as algorithmic opacity, data bias, lack of robust validation, and inequitable access. Conclusions: The integration of artificial intelligence into thoracic oncology requires the combination of clinical judgment, computational capacity, and ethical governance to achieve and equitable and sustainable impact.