Background Transfer learning (TL) with convolutional neural networks aims to improve
performances on a new task by leveraging the knowledge of similar tasks learned in …

Radiomics and machine learning–based methods offer exciting opportunities for improving
diagnostic performance and efficiency in musculoskeletal radiology for various tasks …

Background: Breast ultrasound is the first choice for breast tumor diagnosis in China, but the
Breast Imaging Reporting and Data System (BI-RADS) categorization routinely used in the …

Deep learning with convolutional neural networks (CNN) is a rapidly advancing subset of
artificial intelligence that is ideally suited to solving image-based problems. There are an …

Deep learning-based MRI diagnosis of internal joint derangement is an emerging field of
artificial intelligence, which offers many exciting possibilities for musculoskeletal radiology. A …

Artificial intelligence is rapidly expanding in all technological fields. The medical field, and
especially diagnostic imaging, has been showing the highest developmental potential …

Deep learning is a subfield of state-of-the-art artificial intelligence (AI) technology, and
multiple deep learning-based AI models have been applied to musculoskeletal diseases …

Simple Summary An early prediction of Breast Cancer Recurrence (BCR) for patients
undergoing neoadjuvant chemotherapy (NACT) could better guide clinicians in the …

Objective Chest CT can display the main pathogenic factors of chronic obstructive
pulmonary disease (COPD), emphysema and airway wall remodeling. This study aims to …

With the recent developments in deep learning and the rapid growth of convolutional neural
networks, artificial intelligence has shown promise as a tool that can transform several …