OBJECTIVE: Deep learning (DL) MRI reconstruction enables fast scan acquisition with good visual quality, but the diagnostic impact is often not assessed because of large reader study requirements. This study used existing diagnostic DL to assess the ...
BACKGROUND: Observation of child behaviour provides valuable clinical information but often requires rigorous, tedious, repetitive and time expensive protocols. For this reason, tests requiring significant time for administration and rating are rarel...
Medical & biological engineering & computing
May 9, 2024
Motor imagery (MI) based brain-computer interfaces (BCIs) decode the users' intentions from electroencephalography (EEG) to achieve information control and interaction between the brain and external devices. In this paper, firstly, we apply Riemannia...
Journal of imaging informatics in medicine
May 9, 2024
Semantic segmentation of tumours plays a crucial role in fundamental medical image analysis and has a significant impact on cancer diagnosis and treatment planning. UNet and its variants have achieved state-of-the-art results on various 2D and 3D med...
Medical & biological engineering & computing
May 9, 2024
The accurate selection of the ultrasound plane for the fetal head and pubic symphysis is critical for precisely measuring the angle of progression. The traditional method depends heavily on sonographers manually selecting the imaging plane. This proc...
The journal of trauma and acute care surgery
May 9, 2024
BACKGROUND: Hemorrhage is a leading cause of preventable death in trauma. Accurately predicting a patient's blood transfusion requirement is essential but can be difficult. Machine learning (ML) is a field of artificial intelligence that is emerging ...
The Journal of laryngology and otology
May 9, 2024
OBJECTIVES: This study aimed to determine which machine learning model is most suitable for predicting noise-induced hearing loss and the effect of tinnitus on the models' accuracy.
OBJECTIVE: The objective is to determine whether unsupervised machine learning identifies traumatic brain injury (TBI) phenotypes with unique clinical profiles.
Neural networks : the official journal of the International Neural Network Society
May 9, 2024
Occluded person re-identification (Re-ID) is a challenging task, as pedestrians are often obstructed by various occlusions, such as non-pedestrian objects or non-target pedestrians. Previous methods have heavily relied on auxiliary models to obtain i...
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