The Current and Future State of AI Interpretation of Medical Images | New England Journal of
Medicine Skip to main content The New England Journal of Medicine homepage Advanced …

Digital technologies change the healthcare environment, with several studies suggesting
barriers and facilitators to using digital interventions by healthcare professionals (HPs). We …

Gastric cancer is a leading contributor to cancer incidence and mortality globally. Recently,
artificial intelligence approaches, particularly machine learning and deep learning, are …

Peritoneal surface malignancies (PSMs) are usually associated with a poor prognosis.
Nonetheless, in line with advances in the management of most abdominopelvic metastatic …

Background This study aims to develop an attention-based deep learning model for
distinguishing benign from malignant breast lesions on CESM. Methods Preoperative CESM …

The rapid advances in deep learning-based computational pathology and radiology have
demonstrated the promise of using whole slide images (WSIs) and radiology images for …

Purpose To develop and assess a deep convolutional neural network (DCNN) model for the
automatic detection of bone metastases from lung cancer on computed tomography (CT) …

Objective This study aimed to establish a risk prediction model for diabetic retinopathy (DR)
in the Chinese type 2 diabetes mellitus (T2DM) population using few inspection indicators …

Background Early prediction of lymph node status after neoadjuvant chemotherapy (NAC)
facilitates promptly optimization of treatment strategies. This study aimed to develop and …

Peritoneal recurrence is the most frequent and lethal recurrence pattern in gastric cancer
(GC) with serosal invasion after radical surgery. However, current evaluation methods are …