Deep Learning Models for Predicting Malignancy Risk in CT-Detected Pulmonary Nodules: A Systematic Review and Meta-analysis.

Background: There has been growing interest in using artificial intelligence/deep learning (DL) to help diagnose prevalent diseases earlier. In this study we sought to survey the landscape of externally validated DL-based computer-aided diagnostic (CADx) models, and assess their diagnostic performance for predicting the risk of malignancy in computed tomography (CT)-detected pulmonary nodules.

Methods: An electronic search was performed in four databases (from inception to 10 August 2023).

The role of surgery after prolonged primary chemotherapy for advanced oesophageal adenocarcinoma.

Background: Most patients presenting with oesophageal cancer do so with advanced disease not suitable for surgery. However, there are examples of encouraging survival following surgery in highly selected patients who respond well to chemotherapy.

Methods: This was a retrospective cohort study of patients who presented with advanced but nonvisceral metastatic oesophageal cancer.