Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called ‘long
COVID’, are rising but little is known about prevalence, risk factors or whether it is possible …

Deep-learning has proved in recent years to be a powerful tool for image analysis and is
now widely used to segment both 2D and 3D medical images. Deep-learning segmentation …

Background Data for front-line health-care workers and risk of COVID-19 are limited. We
sought to assess risk of COVID-19 among front-line health-care workers compared with the …

A total of 2,618,862 participants reported their potential symptoms of COVID-19 on a
smartphone-based app. Among the 18,401 who had undergone a SARS-CoV-2 test, the proportion …

Data-driven machine learning (ML) has emerged as a promising approach for building
accurate and robust statistical models from medical data, which is collected in huge volumes by …

International challenges have become the de facto standard for comparative assessment of
image analysis algorithms. Although segmentation is the most widely investigated medical …

Semantic segmentation of medical images aims to associate a pixel with a label in a medical
image without human initialization. The success of semantic segmentation algorithms is …

… M Jorge Cardoso , M Jorge Cardoso … Arman Eshaghi, Razvan V Marinescu, Alexandra L
Young, Nicholas C Firth, Ferran Prados, M Jorge Cardoso, Carmen Tur, Floriana De Angelis, …

This book constitutes the refereed joint proceedings of the Third International Workshop on
Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop …

Background and objectives Medical image analysis and computer-assisted intervention
problems are increasingly being addressed with deep-learning-based solutions. Established …