The COVID-19 pandemic has challenged institutions' diagnostic processes worldwide. The aim of this study was to assess the feasibility of an artificial intelligence (AI)-based software tool that automatically evaluates chest computed tomography for f...
This retrospective analysis was conducted on clinical obtained DCE-MR images of 198 patients, age from 21 to 79 years(45.5±13.7). The CBAM-ResNet model was developed to perform the classification automatically at the image-level based on deep learnin...
Journal of the American Medical Informatics Association : JAMIA
Oct 12, 2021
OBJECTIVE: Artificial intelligence (AI) and machine learning (ML) enabled healthcare is now feasible for many health systems, yet little is known about effective strategies of system architecture and governance mechanisms for implementation. Our obje...
Virtual clinical trials (VCTs) can be used to evaluate and optimise medical imaging systems. VCTs are based on computer simulations of human anatomy, imaging modalities and image interpretation. OpenVCT is an open-source framework for conducting VCTs...
This paper is concerned with the role of science and technology in helping to create change in society. Diagnostic radiology is an example of an activity that has undergone significant change due to such developments, which over the past 40 years hav...
Zhonghua bing li xue za zhi = Chinese journal of pathology
Oct 8, 2021
To explore the performance of the attention-multiple instance learning (MIL) framework, an attention fusion network-based MIL, in the automated diagnosis of chronic gastritis with multiple indicators. A total of 1 015 biopsy cases of gastritis diag...
The field of cardiac electrophysiology (EP) had adopted simple artificial intelligence (AI) methodologies for decades. Recent renewed interest in deep learning techniques has opened new frontiers in electrocardiography analysis including signature id...
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