The Use of Artificial Intelligence and Machine Learning in Thoracic Surgery

Area of Science:

• Thoracic Surgery
• Artificial Intelligence
• Medical Technology

Background:

• Artificial intelligence (AI) is rapidly advancing and presents significant opportunities within thoracic surgery.
• Current utilization of AI tools in thoracic surgery remains suboptimal, indicating a need for broader integration and understanding.

Purpose of the Study:

• To provide a foundational overview of artificial intelligence principles.
• To explore the diverse applications of AI across the spectrum of thoracic surgical care.
• To highlight the potential of AI in improving accuracy and safety in thoracic surgery.

Main Methods:

• Literature review and synthesis of existing research on AI in thoracic surgery.
• Categorization of AI applications based on surgical phases: preoperative, intraoperative, and postoperative.
• Analysis of current research trends, focusing on lung and esophageal cancer applications.

Main Results:

• AI applications span preoperative diagnosis, intraoperative guidance, and postoperative prognosis prediction.
• AI integration aims to enhance diagnostic accuracy and surgical safety.
• Current research predominantly focuses on lung and esophageal cancers, with broader potential across thoracic diseases.

Conclusions:

• AI holds substantial promise for revolutionizing thoracic surgery by improving patient outcomes.
• Further research and implementation are needed to fully leverage AI's capabilities in thoracic surgery.
• Expanding AI applications beyond current focuses can benefit a wider range of thoracic conditions.