BACKGROUND: Several studies have been published comparing deep learning (DL)/machine learning (ML) to radiologists in differentiating PCNSLs from GBMs with equivocal results. We aimed to perform this meta-analysis to evaluate the diagnostic accuracy ...
The integration of artificial intelligence (AI) in medical image interpretation requires effective collaboration between clinicians and AI algorithms. Although previous studies demonstrated the potential of AI assistance in improving overall clinicia...
PURPOSE: Segmentation of hepatocellular carcinoma (HCC) is crucial; however, manual segmentation is subjective and time-consuming. Accurate and automatic lesion contouring for HCC is desirable in clinical practice. In response to this need, our study...
Journal of medical imaging and radiation sciences
Feb 24, 2024
Uncertainty regarding the future of radiologists is largely driven by the emergence of artificial intelligence (AI). If AI succeeds, will radiologists continue to monopolize imaging services? As AI accuracy progresses with alacrity, radiology reads w...
Artificial intelligence (AI) is infiltrating nearly all fields of science by storm. One notorious property that AI algorithms bring is their so-called black box character. In particular, they are said to be inherently unexplainable algorithms. Of cou...
Journal of imaging informatics in medicine
Feb 21, 2024
Segmentation of glioma is crucial for quantitative brain tumor assessment, to guide therapeutic research and clinical management, but very time-consuming. Fully automated tools for the segmentation of multi-sequence MRI are needed. We developed and p...
Journal of imaging informatics in medicine
Feb 8, 2024
This study aimed to assess the performance of a deep learning algorithm in helping radiologist achieve improved efficiency and accuracy in chest radiograph diagnosis. We adopted a deep learning algorithm to concurrently detect the presence of normal ...
Early and accurate diagnosis of focal liver lesions is crucial for effective treatment and prognosis. We developed and validated a fully automated diagnostic system named Liver Artificial Intelligence Diagnosis System (LiAIDS) based on a diverse samp...
In healthcare, artificial intelligence (AI) is expected to improve work processes, yet most research focuses on the technical features of AI rather than its real-world clinical implementation. To evaluate the implementation process of an AI-based com...
PURPOSE: Although several studies have compared the performance of deep learning (DL) models and radiologists for the diagnosis of COVID-19 pneumonia on CT of the chest, these results have not been collectively evaluated. We performed a meta-analysis...
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