Artificial Intelligence (AI) and Machine Learning in Thoracic Surgery: the Link between Surgical Oncology and Personalized Medicine

Artificial intelligence (AI) and machine learning (ML) are widely considered to wield tremendous potential in the medical field in terms of improving diagnoses, surgical practices, and clinical outcomes. AI entails an intelligent computer that simulates human tasks, while machine learning is a process by which a computer can develop its intelligence. The combination of AI and ML may enable medical professionals to detect bodily characteristics with greater precision, improve tactical feedback, and in turn, operate on patients with greater efficiency and effectiveness. In fact, ML has already been implemented as a diagnostic tool to define complex pathological patterns. The synergy between AI and ML will inevitably be important in the development of new machines and tools that will improve patients’ prognoses, survival chances, and quality of life following thoracic surgery, especially relating to thoracic oncology. In particular, AI has shown promising results on patient prognosis focusing on surgical patient management because it implies not only the usefulness of the surgical act planned and proposed to the patient, but also the impact it will have on the patient's short- and long-term outcomes. Moreover, AI opens to new possibilities in radiology, pathology, or respiratory medicine, which are part of the management from the pre-operative and post-operative period, including follow-up. On the other side, machine learning reflects an artificial intelligence that allows ap...