Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging Trends
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 ext...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-10-01
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| Series: | Current Oncology |
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| Online Access: | https://www.mdpi.com/1718-7729/31/10/464 |
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| author | Mohamed Umair Aleem Jibran Ahmad Khan Asser Younes Belal Nedal Sabbah Waleed Saleh Marcello Migliore |
| author_facet | Mohamed Umair Aleem Jibran Ahmad Khan Asser Younes Belal Nedal Sabbah Waleed Saleh Marcello Migliore |
| author_sort | Mohamed Umair Aleem |
| collection | DOAJ |
| description | 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 record (EMR) data. Moreover, AI applications in robotic-assisted thoracic surgery (RATS) and perioperative management reveal the potential to improve 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 perioperative 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. |
| format | Article |
| id | doaj-art-8580bc2811074df5959e4e22cdfe4fb1 |
| institution | OA Journals |
| issn | 1198-0052 1718-7729 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Current Oncology |
| spelling | doaj-art-8580bc2811074df5959e4e22cdfe4fb12025-08-20T02:11:09ZengMDPI AGCurrent Oncology1198-00521718-77292024-10-0131106232624410.3390/curroncol31100464Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging TrendsMohamed Umair Aleem0Jibran Ahmad Khan1Asser Younes2Belal Nedal Sabbah3Waleed Saleh4Marcello Migliore5College of Medicine, Alfaisal University, Riyadh 11533, Saudi ArabiaCollege of Medicine, Alfaisal University, Riyadh 11533, Saudi ArabiaThoracic Surgery & Lung Transplant, Lung Health Centre, Organ Transplant Center of Excellence (OTCoE), King Faisal Specialist Hospital & Research Center, Riyadh 11211, Saudi ArabiaCollege of Medicine, Alfaisal University, Riyadh 11533, Saudi ArabiaThoracic Surgery & Lung Transplant, Lung Health Centre, Organ Transplant Center of Excellence (OTCoE), King Faisal Specialist Hospital & Research Center, Riyadh 11211, Saudi ArabiaThoracic Surgery & Lung Transplant, Lung Health Centre, Organ Transplant Center of Excellence (OTCoE), King Faisal Specialist Hospital & Research Center, Riyadh 11211, Saudi ArabiaArtificial 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 record (EMR) data. Moreover, AI applications in robotic-assisted thoracic surgery (RATS) and perioperative management reveal the potential to improve 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 perioperative 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.https://www.mdpi.com/1718-7729/31/10/464thoracic surgeryAIartificial intelligenceVATSRATSprecision medicine |
| spellingShingle | Mohamed Umair Aleem Jibran Ahmad Khan Asser Younes Belal Nedal Sabbah Waleed Saleh Marcello Migliore Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging Trends Current Oncology thoracic surgery AI artificial intelligence VATS RATS precision medicine |
| title | Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging Trends |
| title_full | Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging Trends |
| title_fullStr | Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging Trends |
| title_full_unstemmed | Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging Trends |
| title_short | Enhancing Thoracic Surgery with AI: A Review of Current Practices and Emerging Trends |
| title_sort | enhancing thoracic surgery with ai a review of current practices and emerging trends |
| topic | thoracic surgery AI artificial intelligence VATS RATS precision medicine |
| url | https://www.mdpi.com/1718-7729/31/10/464 |
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