The aim of our study was to evaluate the specific performance of an artificial intelligence (AI) algorithm for lung nodule detection in chest radiography for a larger number of nodules of different sizes and densities using a standardized phantom app...
BACKGROUND AND AIMS: The significance of left ventricular mass and chamber volumes from non-contrast computed tomography (CT) for predicting major adverse cardiovascular events (MACE) has not been studied. Our objective was to evaluate the role of ar...
INTRODUCTION: A chest X-ray (CXR) is the most common imaging investigation performed worldwide. Advances in machine learning and computer vision technologies have led to the development of several artificial intelligence (AI) tools to detect abnormal...
International journal of computer assisted radiology and surgery
39812891
PURPOSE: Breast cancer remains one of the most prevalent cancers globally, necessitating effective early screening and diagnosis. This study investigates the effectiveness and generalizability of our recently proposed data augmentation technique, att...
PURPOSE: We aimed to validate a clinically available artificial intelligence (AI) model to assist general radiologists in the detection of intracranial aneurysm (IA) in a multi-reader multi-case (MRMC) study, and to explore its performance in routine...
Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
39812675
UNLABELLED: This study utilized deep learning for bone mineral density (BMD) prediction and classification using biplanar X-ray radiography (BPX) images from Huashan Hospital Medical Checkup Center. Results showed high accuracy and strong correlation...
Quantifying pleural effusion change at chest CT is important for evaluating disease severity and treatment response. The purpose of this study was to assess the accuracy of artificial intelligence (AI)-based volume quantification of pleural effusion ...
Purpose To evaluate the change in digital breast tomosynthesis artificial intelligence (DBT-AI) case scores over sequential screenings. Materials and Methods This retrospective review included 21 108 female patients (mean age ± SD, 58.1 years ± 11.5)...
The aim of this technical report was to assess whether the "Radiological Report" tool within the Artificial Intelligence (AI) software Diagnocat can achieve a satisfactory level of performance comparable to that of experienced dentomaxillofacial radi...
PURPOSE: Radiological follow-up of oncology patients requires the detection of metastatic lung lesions and the quantitative analysis of their changes in longitudinal imaging studies. Our aim was to evaluate SimU-Net, a novel deep learning method for ...