Latest AI and machine learning research in thoracic surgery for healthcare professionals.
Cardiomegaly screening via manual Cardiothoracic Ratio (CTR) measurement remains a clinical bottleneck, while contemporary deep learning solutions often suffer from algorithmic bloating. To address the need for resource-efficient and interpretable triage, this study proposes a framework driven by implicit morphological inference, which bypasses the requirement for explicit heart segmentation. We d...
BACKGROUND: Postoperative atrial fibrillation (POAF) is a common and serious complication following video-assisted thoracoscopic surgery (VATS), which affects patients' medical outcomes and quality of life. The predictive value of high-sensitivity C-reactive protein (hs-CRP) as an inflammatory marker for POAF in non-cardiac surgeries remains unclear. This study aims to investigate the association ...
BACKGROUND: Curative treatment of resectable esophageal cancer comprises neoadjuvant chemoradiotherapy and esophagectomy. Robot-assisted minimally inv...
Spread through air spaces (STAS) is a recently recognized pattern of invasion in lung cancer that is strongly linked to postoperative recurrence and p...
INTRODUCTION: Conventional risk scores like EuroSCORE II and Society of Thoracic Surgeons models, derived from logistic regression, may not fully repr...
The increasing complexity of cardiovascular procedures, regulatory constraints, and heightened patient safety requirements have necessitated a fundame...
Purpose To evaluate the accuracy and time efficiency of a deep learning (DL)-based tool for automated quantification of functional small airway diseas...
Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is the standard minimally invasive modality for mediastinal staging in no...
BACKGROUND: Although an artificial intelligence-driven three-dimensional reconstruction system (AI-3D) facilitates preoperative planning, its impact o...
BACKGROUND: Postoperative pulmonary complications (PPCs), including pneumonia, acute lung injury, and acute respiratory distress syndrome, are common ...
Canadian radiology continues to produce scholarship that is technically sophisticated, clinically relevant, and increasingly attentive to the wider sy...
Fluid overload is common after neonatal congenital cardiac surgery (CCS) and is frequently managed with continuous furosemide infusions requiring iter...
Existing methods of grading atelectasis are typically subjective and not scalable. We aimed to develop an automated, deep learning-based framework to ...
PURPOSE: Despite recent advances in preoperative work-up of drug resistant medial temporal lobe epilepsy (MTLE), predicting post-surgical seizure and ...
BACKGROUND: Accurate prediction of pathological complete response (pCR) after preoperative chemoradiation therapy, followed by surgery (trimodality th...
OBJECTIVE: This study evaluates the performance of an artificial intelligence predictive clinical decision support system (CheLSEA) in generating ches...
BACKGROUND: We implemented a prospective screening program to detect deep venous thromboembolism and define its prevalence in patients with esophageal...
BACKGROUND: In clinical stage IA lung adenocarcinoma (LUAD), rapid and accurate intraoperative diagnosis is crucial to decide whether to perform segme...
Patients undergoing cardiothoracic and vascular surgery are at uniquely high risk for postoperative pulmonary complications due to the confluence of s...
BACKGROUND: Gender disparities in academic surgery persist, particularly in authorship positions that signal leadership, mentorship, and scholarly inf...