Latest AI and machine learning research in thoracic surgery for healthcare professionals.
OBJECTIVE: To develop a deep learning algorithm for anatomy recognition in thoracoscopic video frames from robot-assisted minimally invasive esophagectomy (RAMIE) procedures using deep learning.
BACKGROUND AND OBJECTIVES: Bedside chest radiographs (CXRs) are challenging to interpret but important for monitoring cardiothoracic disease and invasive therapy devices in critical care and emergency medicine. Taking surrounding anatomy into account is likely to improve the diagnostic accuracy of artificial intelligence and bring its performance closer to that of a radiologist. Therefore, we aime...
Robot-assisted thoracic surgery (RATS) for higher stages non-small cell lung carcinoma (NSCLC) remains controversial. This study reports the feasibili...
Robot-assisted minimally invasive esophagectomy (RAMIE) is increasingly becoming established as a standard procedure in surgical centers for esophagec...
Artificial intelligence algorithms can learn by assimilating information from large datasets in order to decipher complex associations, identify previ...
PURPOSE: Most robot-assisted thoracoscopic surgery (RATS) is performed from the vertical view. This study evaluates the initial outcomes of our novel ...
BACKGROUND: Currently, little is known regarding the optimal technique for the abdominal phase of RAMIE. The aim of this study was to investigate the ...
BACKGROUND: To assess the feasibility, clinical utility, and safety of intrathoracic robotic-sewn esophageal anastomosis (IrEA) during Ivor Lewis esop...
BACKGROUND: In the West, patients with cervical lymph node metastasis of resectable esophageal cancer at diagnosis are generally precluded from curati...
Transthoracic subtotal esophagectomy with two-field lymph node (mediastinal and abdominal) and monobloc posterior mediastinectomy is called Ivor Lewis...
Salvage surgery for esophageal cancer after definitive chemoradiotherapy (dCRT) is effective, but it is associated with a high rate of perioperative c...
BACKGROUND: Studies of robotic lobectomy (Robot-L) have been performed using data from high-volume, specialty centers which may not be generalizable. ...
The new da Vinci® single-port (SP) robotic system, which utilizes a smaller incision and work space compared to the previous versions, is suitable for...
Esophagectomy is the selected treatment for nonmetastatic esophageal and esophagogastric junction cancer, although high perioperative morbidity and mo...
OBJECTIVE: To analyze the short-term effect of Da Vinci robot-assisted thoracoscopic (RATS) bronchial sleeve lobectomy, so as to summarize its safety ...
The use of robotic surgery has increased exponentially in the United States. Despite this uptick in popularity, no standardized training pathway exist...
INTRODUCTION: Sarcopenia is a known risk factor for adverse outcomes after esophageal cancer (EC) surgery. Robot-assisted minimally invasive esophagec...
As robotic-assisted surgery (RAS) expands to smaller centres, platforms are shared between specialities. Healthcare providers must consider case volum...