International journal of paediatric dentistry
May 20, 2024
BACKGROUND: Primary teeth segmentation on cone beam computed tomography (CBCT) scans is essential for paediatric treatment planning. Conventional methods, however, are time-consuming and necessitate advanced expertise.
RATIONALE AND OBJECTIVES: Artificial intelligence (AI) technologies are rapidly evolving and offering new advances almost on a day-by-day basis, including various tools for manuscript generation and modification. On the other hand, these potentially ...
INTRODUCTION: The extraction decision significantly affects the treatment process and outcome. Therefore, it is crucial to make this decision with a more objective and standardized method. The objectives of this study were (1) to identify the best-pe...
Ovarian cancer (OC) is a major cause of cancer mortality in women worldwide. Due to the occult onset of OC, its nonspecific clinical symptoms in the early phase, and a lack of effective early diagnostic tools, most OC patients are diagnosed at an adv...
BACKGROUND: Robot-assisted gait training (RAGT) is promising to help walking rehabilitation in cerebral palsy, but training-induced neuroplastic effects have little been investigated.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
May 20, 2024
Lung cancer screening (LCS) using annual computed tomography (CT) scanning significantly reduces mortality by detecting cancerous lung nodules at an earlier stage. Deep learning algorithms can improve nodule malignancy risk stratification. However, t...
Neural networks : the official journal of the International Neural Network Society
May 20, 2024
Missing modality sentiment analysis is a prevalent and challenging issue in real life. Furthermore, the heterogeneity of multimodality often leads to an imbalance in optimization when attempting to optimize the same objective across all modalities in...
Neural networks : the official journal of the International Neural Network Society
May 20, 2024
Multi-source unsupervised domain adaptation aims to transfer knowledge from multiple labeled source domains to an unlabeled target domain. Existing methods either seek a mixture of distributions across various domains or combine multiple single-sourc...
Neural networks : the official journal of the International Neural Network Society
May 20, 2024
To enhance the model's generalization ability in unsupervised domain adaptive segmentation tasks, most approaches have primarily focused on pixel-level local features, but neglected the clue in category information. This limitation results in the seg...
Neural networks : the official journal of the International Neural Network Society
May 20, 2024
Although existing reconstruction-based multivariate time series anomaly detection (MTSAD) methods have shown advanced performance, most assume the training data is clean. When faced with noise or contamination in training data, they can also reconstr...
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