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...

Full description

Saved in:
Bibliographic Details
Main Authors: Mohamed Umair Aleem, Jibran Ahmad Khan, Asser Younes, Belal Nedal Sabbah, Waleed Saleh, Marcello Migliore
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Current Oncology
Subjects:
Online Access:https://www.mdpi.com/1718-7729/31/10/464
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850205107207012352
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
work_keys_str_mv AT mohamedumairaleem enhancingthoracicsurgerywithaiareviewofcurrentpracticesandemergingtrends
AT jibranahmadkhan enhancingthoracicsurgerywithaiareviewofcurrentpracticesandemergingtrends
AT asseryounes enhancingthoracicsurgerywithaiareviewofcurrentpracticesandemergingtrends
AT belalnedalsabbah enhancingthoracicsurgerywithaiareviewofcurrentpracticesandemergingtrends
AT waleedsaleh enhancingthoracicsurgerywithaiareviewofcurrentpracticesandemergingtrends
AT marcellomigliore enhancingthoracicsurgerywithaiareviewofcurrentpracticesandemergingtrends