Thoracic Surgery

Development and validation of a nomogram model to predict postoperative delirium after resection of esophageal cancer.

The study aimed to establish and validate a nomogram model to predict postoperative delirium (POD) a...

Evaluation of AI-based detection of incidental pulmonary emboli in cardiac CT angiography scans.

Incidental pulmonary embolism (PE) is detected in 1% of cardiac CT angiography (CCTA) scans, despite...

Impact of Artificial Intelligence on the Timing of Recurrent Laryngeal Nerve Recognition during Robot-Assisted Minimally Invasive Esophagectomy.

BACKGROUND: As a first step to prevent recurrent laryngeal nerve (RLN) palsy, we have developed an a...

Real-time AI-based detection of excessive traction on the recurrent laryngeal nerve during robotic-assisted minimally invasive esophagectomy: a proof-of-concept study.

Recurrent laryngeal nerve (RLN) palsy often occurs due to excessive traction (ET) on the nerve durin...

The Year in Graduate Medical Education: Selected Highlights from 2024.

This special article is the fourth in an annual series for the Journal of Cardiothoracic and Vascula...

Role of VATS-US in identifying and characterizing pulmonary nodules: a narrative review.

The aim of this study was to show the efficacy described in the scientific literature of lung ultras...

Modern statistical techniques for cardiothoracic surgeons: Part 8-Bayesian analysis and beyond.

Bayesian analysis is a statistical approach that updates the probability of a hypothesis as new evid...

AI-based measurement of cardiothoracic ratio in chest X-rays and prediction of echocardiographic congestive heart failure.

BACKGROUND: This study presents an artificial intelligence (AI) model for automated cardiothoracic r...

The Year in Perioperative Echocardiography: Selected Highlights from 2024.

This article is the ninth of an annual series reviewing the research highlights of the year pertaini...

Artificial intelligence for intraoperative video analysis in robotic-assisted esophagectomy.

BACKGROUND: Robotic-assisted minimally invasive esophagectomy (RAMIE) is a complex surgical procedur...

Letter to the editor regarding the article "learning curve for robot-assisted Mckeown esophagectomy in patients with thoracic esophageal cancer".

Early prediction of 30-day mortality in patients with surgical wound infections following cardiothoracic surgery: Development and validation of the SWICS-30 score utilizing conventional logistic regression and artificial neural network.

INTRODUCTION: We aimed to create and validate the 30-day prognostic score for mortality in patients ...

Soft-tissue metastasis in esophageal cancer managed by dose escalation radiation therapy: a clinical case and review of literature.

Soft tissue metastasis in esophageal cancer is a very rare entity. A 76-year-old man was referred fo...

Prognostic Impact of Tumor Cell Nuclear Size Assessed by Artificial Intelligence in Esophageal Squamous Cell Carcinoma.

Tumor cell nuclear size (NS) indicates malignant potential in breast cancer; however, its clinical s...

Automated measurement of cardiothoracic ratio based on semantic segmentation integration model using deep learning.

The objective of this study is to investigate the efficacy of the semantic segmentation model in pre...

Utilizing machine learning approaches to investigate the relationship between cystatin C and serious complications in esophageal cancer patients after esophagectomy.

BACKGROUND: The purpose of this study is to investigate the relationship between preoperative cystat...

Diagnostic modalities in the mediastinum and the role of bronchoscopy in mediastinal assessment: a narrative review.

BACKGROUND AND OBJECTIVE: Diagnosis of pathology in the mediastinum has proven quite challenging, gi...

Extraction and evaluation of features of preterm patent ductus arteriosus in chest X-ray images using deep learning.

Echocardiography is the gold standard of diagnosis and evaluation of patent ductus arteriosus (PDA),...

Preoperative markers for identifying CT ≤2 cm solid nodules of lung adenocarcinoma based on image deep learning.

BACKGROUND: The solid pattern is a highly malignant subtype of lung adenocarcinoma. In the current e...

Usefulness of an Artificial Intelligence Model in Recognizing Recurrent Laryngeal Nerves During Robot-Assisted Minimally Invasive Esophagectomy.

BACKGROUND: Recurrent laryngeal nerve (RLN) palsy is a common complication in esophagectomy and its ...

Deep learning prediction of survival in patients with heart failure using chest radiographs.

Heart failure (HF) is associated with high rates of morbidity and mortality. The value of deep learn...