Development and validation of open-source deep neural networks for comprehensive chest x-ray reading: a retrospective, multicentre study.

Background: Artificial intelligence (AI) systems for automated chest x-ray interpretation hold promise for standardising reporting and reducing delays in health systems with shortages of trained radiologists. Yet, there are few freely accessible AI systems trained on large datasets for practitioners to use with their own data with a view to accelerating clinical deployment of AI systems in radiology. We aimed to contribute an AI system for comprehensive chest x-ray abnormality detection.

Exercise prehabilitation during neoadjuvant chemotherapy may enhance tumour regression in oesophageal cancer: results from a prospective non-randomised trial.

Background: There is increasing evidence for the use of exercise in cancer patients and data supporting enhanced tumour volume reduction following chemotherapy in animal models. To date, there is no reported histopathological evidence of a similar oncological benefit in oesophageal cancer.

Methods: A prospective non-randomised trial compared a structured prehabilitation exercise intervention during neoadjuvant chemotherapy and surgery versus conventional best-practice for oesophageal cancer patients.