Artificial Intelligence in Oncologic Thoracic Surgery: Clinical Decision Support and Emerging Applications. - Petrella, Francesco; Rizzo, Stefania (Cancers, 2026)
Simple Summary: Artificial intelligence (AI) is changing the way surgeons perform chest surgery, including operations on the lungs and other organs in the chest. AI uses computers to help surgeons make better decisions, plan surgeries, and even guide them during operations. For example, AI can help spot lung cancer earlier by analyzing scans and test results more quickly and accurately than before. During surgery, smart robots and computer programs can help surgeons be more precise, making the surgery safer and helping patients recover faster. After surgery, AI can help physicians watch for problems and predict which patients might need extra care, using information from wearable devices and medical records. While these new tools are promising, there are still challenges. AI needs to be tested widely to make sure it works for everyone, and physicians must be careful about privacy and fairness. Some computer programs can make mistakes or be hard to understand, so experts are working to make AI safer and easier to use. Overall, AI is helping medical doctors to improve care for people who need chest surgery, but more research and careful planning are needed before these tools become a regular part of medical practice. Artificial intelligence (AI) is rapidly reshaping thoracic surgery, advancing from decision support to the threshold of autonomous intervention. AI-driven technologies—including machine learning (ML), deep learning (DL), and computer vision—have demonstrated significant improvements in diagnostic accuracy, surgical planning, intraoperative navigation, and postoperative outcome prediction. In lung cancer and thoracic oncology, AI enhances imaging analysis, histopathological classification, and risk stratification, supporting multidisciplinary decision-making and personalized therapy. Robotic-assisted and AI-guided systems are optimizing surgical precision and workflow efficiency, while real-time decision-support tools and augmented reality are improving intraoperative safety. Despite these advances, widespread adoption is limited by challenges in algorithmic bias, data integration, regulatory approval, and ethical transparency. The literature emphasizes the need for multicenter validation, explainable AI, and robust governance frameworks to ensure safe and effective clinical integration. Future research should focus on digital twin technology, federated learning, and transparent AI outputs to further enhance reliability and accessibility. AI is poised to transform thoracic surgery, but responsible implementation and ongoing evaluation are essential for realizing its full potential. The aim of this review is to evaluate and synthesize the current landscape of artificial intelligence (AI) applications across the thoracic surgical pathway, from preoperative decision-support to intraoperative guidance and emerging autonomous interventions.