ReviewSurgery in practice and science2025
Artificial intelligence in thoracic surgery: Perspectives and challenges.
Review in Surgery in practice and science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the advances of artificial intelligence (AI) in the medical field, particularly the widespread utilization of large language models (LLMs) such as ChatGPT, Claude, Gemini, Llama, and Deepseek, clinical practice is undergoing an unprecedented technological revolution. These cutting-edge technologies facilitate efficient processing and analysis of vast datasets, providing medical professionals with auxiliary diagnoses and treatment suggestions, while markedly enhancing the quality and efficiency of medical services. Over the past decade, the field of thoracic surgery has achieved transformative progress, primarily driven by AI innovations. Consequently, thoracic surgeons must possess a foundational understanding of AI in order to grasp its implications on their daily practice and explore potential ways of integrating this technology into their work. This article reviews the fundamental elements of AI and the relationships between AI-based techniques. It further summarizes the application of AI in thoracic surgery, aiming to enhance thoracic surgeons' comprehensive understanding of the latest developments in this area. Additionally, this article explores the challenges and limitations faced by AI, including data security and privacy concerns, issues of bias and discrimination, challenges in verification and interpretability, ethical and legal considerations, technical obstacles, as well as training and educational requirements. Finally, it explores emerging AI architectures and their paradigm-shifting impacts on medical ecosystems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.