Version 1
: Received: 3 September 2024 / Approved: 3 September 2024 / Online: 5 September 2024 (06:22:20 CEST)
How to cite:
Aleem, M. U.; Khan, J. A.; Asser Younes, A. Y.; Sabbah, B. N.; Saleh, W.; Migliore, M. Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging Trends. Preprints2024, 2024090271. https://doi.org/10.20944/preprints202409.0271.v1
Aleem, M. U.; Khan, J. A.; Asser Younes, A. Y.; Sabbah, B. N.; Saleh, W.; Migliore, M. Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging Trends. Preprints 2024, 2024090271. https://doi.org/10.20944/preprints202409.0271.v1
Aleem, M. U.; Khan, J. A.; Asser Younes, A. Y.; Sabbah, B. N.; Saleh, W.; Migliore, M. Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging Trends. Preprints2024, 2024090271. https://doi.org/10.20944/preprints202409.0271.v1
APA Style
Aleem, M. U., Khan, J. A., Asser Younes, A. Y., Sabbah, B. N., Saleh, W., & Migliore, M. (2024). Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging Trends. Preprints. https://doi.org/10.20944/preprints202409.0271.v1
Chicago/Turabian Style
Aleem, M. U., Waleed Saleh and Marcello Migliore. 2024 "Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging Trends" Preprints. https://doi.org/10.20944/preprints202409.0271.v1
Abstract
Artificial Intelligence (AI) is increasingly becoming integral to medical practice, potentially enhancing outcomes in thoracic surgery. AI-driven models have shown significant accuracy in diagnosing non-small cell lung cancer (NSCLC), predicting lymph node metastasis, and aiding in the efficient extraction of electronic medical records (EMR) data. Moreover, AI applications in robotic-assisted thoracic surgery (RATS) and perioperative management reveal potential in improving surgical precision, patient safety, and overall care efficiency. Despite these advancements, challenges such as data privacy, biases, and ethical concerns remain. This manuscript explores AI applications, particularly machine learning (ML) and natural language processing (NLP), in thoracic surgery, emphasizing their role in diagnosis and peri-operative management. It also provides a comprehensive overview of the current state, benefits, and limitations of AI in thoracic surgery, highlighting future directions in the field.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.