Alzheimer's & dementia : the journal of the Alzheimer's Association
Jul 6, 2023
BACKGROUND: Identifying genetic patterns that contribute to Alzheimer's disease (AD) is important not only for pre-symptomatic risk assessment but also for building personalized therapeutic strategies.
In recent years, artificial intelligence, particularly deep learning (DL), has demonstrated utility in diverse areas of medicine. DL uses neural networks to automatically learn features from the raw data while this is not possible with conventional m...
OBJECTIVES: This study developed and validated a deep learning-based method to automatically segment and number teeth in panoramic radiographs across primary, mixed, and permanent dentitions.
AJNR. American journal of neuroradiology
Jul 6, 2023
BACKGROUND AND PURPOSE: Deep learning image reconstruction allows faster MR imaging acquisitions while matching or exceeding the standard of care and can create synthetic images from existing data sets. This multicenter, multireader spine study evalu...
BMC medical informatics and decision making
Jul 6, 2023
Deep learning models have been widely used in electroencephalogram (EEG) analysis and obtained excellent performance. But the adversarial attack and defense for them should be thoroughly studied before putting them into safety-sensitive use. This wor...
Shape measurements are crucial for evolutionary and developmental biology; however, they present difficulties in the objective and automatic quantification of arbitrary shapes. Conventional approaches are based on anatomically prominent landmarks, wh...
The evaluation of animals' motion behavior has played a vital role in neuromuscular biomedical research and clinical diagnostics, which reflects the changes caused by neuromodulation or neurodamage. Currently, the existing animal pose estimation meth...
IEEE transactions on neural networks and learning systems
Jul 6, 2023
The simultaneous-source technology for high-density seismic acquisition is a key solution to efficient seismic surveying. It is a cost-effective method when blended subsurface responses are recorded within a short time interval using multiple seismic...
IEEE transactions on neural networks and learning systems
Jul 6, 2023
Passive seismic interferometry is a vastly generalized blind deconvolution question, where different paths through the Earth correspond to different channels called Green's functions; the sources are completely incoherent and not shared by the channe...
IEEE transactions on neural networks and learning systems
Jul 6, 2023
Numerical models based on physics represent the state of the art in Earth system modeling and comprise our best tools for generating insights and predictions. Despite rapid growth in computational power, the perceived need for higher model resolution...
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