OBJECTIVE: T1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is time consuming and prone to subjective errors. Therefore, this study aimed to test a DL algorithm for the automated measurement of native T1 and extrace...
Journal of the American Medical Informatics Association : JAMIA
Nov 14, 2022
OBJECTIVE: Alzheimer's disease (AD) is the most common neurodegenerative disorder with one of the most complex pathogeneses, making effective and clinically actionable decision support difficult. The objective of this study was to develop a novel mul...
In order to achieve better performance, artificial intelligence is used in breast cancer diagnosis. In this study, we evaluated the efficacy of different fine-tuning strategies of deep transfer learning (DTL) based on the DenseNet201 model to differe...
BACKGROUND: Transforaminal epidural steroid injections (TFESI) are widely used to alleviate lumbosacral radicular pain. Knowledge of the therapeutic outcomes of TFESI allows clinicians to elucidate therapeutic plans for managing lumbosacral radicular...
OBJECTIVE: The aim of this study was to develop a deep learning algorithm for detection of active inflammatory sacroiliitis in short tau inversion recovery (STIR) sequence MRI.
Quantitative magnetic resonance imaging (qMRI) has been shown to provide many potential advantages for personalized adaptive radiotherapy (RT). Deep learning models have proven to increase efficiency, robustness and speed for different qMRI tasks. Th...
BACKGROUND: Accurate detection is essential for brain metastasis (BM) management, but manual identification is laborious. This study developed, validated, and evaluated a BM detection (BMD) system.
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