Artificial intelligence in thoracic surgery: Perspectives and challenges.

Area of Science:

• Medical Informatics
• Artificial Intelligence
• Thoracic Surgery

Background:

• The medical field is experiencing a technological revolution driven by artificial intelligence (AI) and large language models (LLMs).
• AI facilitates efficient data processing, offering auxiliary diagnoses and treatment suggestions, enhancing medical service quality and efficiency.
• Thoracic surgery has seen significant progress due to AI innovations over the last decade.

Purpose of the Study:

• To review fundamental AI elements and their relationships.
• To summarize AI applications in thoracic surgery.
• To enhance thoracic surgeons' understanding of AI developments and integration.

Main Methods:

• Review of AI fundamentals and AI-based techniques.
• Summary of AI applications specifically within thoracic surgery.
• Exploration of challenges, limitations, and emerging AI architectures.

Main Results:

• AI and LLMs are transforming clinical practice by improving data analysis and decision support.
• AI has driven significant advancements in thoracic surgery over the past decade.
• Various challenges exist, including data security, bias, interpretability, ethics, and training.

Conclusions:

• Thoracic surgeons need a foundational understanding of AI to leverage its benefits and navigate its integration.
• Emerging AI architectures promise paradigm-shifting impacts on the broader medical ecosystem.
• Addressing AI's limitations is essential for its responsible and effective implementation in healthcare.