As an emerging technology, artificial intelligence (AI) uses human theory and technology for robots to study, develop, learn and identify human technologies. Thoracic surgeons should be aware of new opportunities that may affect their daily practice by the direct use of AI technology, or indirect use in the relevant medical fields (radiology, pathology, and respiratory medicine). The purpose of this paper is to review the application status and future development of AI associated with thoracic surgery, diagnosis of AI-related lung cancer, prognosis-assisted decision-making programs and robotic surgery. While AI technology has made rapid progress in many areas, the medical industry only accounts for a small part of AI use, and AI technology is gradually becoming widespread in the diagnosis, treatment, rehabilitation, and care of diseases. The future of AI is bright and full of innovative perspectives. The field of thoracic surgery has conducted valuable exploration and practice on AI, and will receive more and more influence and promotion from AI.
With the rapid global development of artificial intelligence (AI) technology, its applications in various industries continue to deepen. Against this backdrop, AI empowering high-quality development in the pharmaceutical and healthcare sector has become a global research hotspot, and AI-enabled health technology assessment (HTA) constitutes a key component of AI applications in the pharmaceutical field. Currently, the World Health Organization (WHO), International Society for Pharmacoeconomics and Outcomes Research (ISPOR), National Institute for Health and Care Excellence (NICE), and Canada’s Drug Agency (CDA-AMC) are all actively exploring the application pathways, technical challenges, developmental limitations, and solutions of AI in HTA. This paper aims to conduct a systematic analysis of AI-related basic concepts and classifications, typical application scenarios of AI in HTA, risk challenges, and position principles, based on the exploratory findings of the aforementioned entities regarding AI applications in HTA and integrating the technical characteristics of AI and HTA themselves. It further seeks to propose the application pathways, directions, and future prospects of AI in China’s HTA field by drawing on international beneficial experiences.