AIMC Topic: Humans

Clear Filters Showing 25571 to 25580 of 95995 articles

Deep learning-based quantification of osteonecrosis using magnetic resonance images in Gaucher disease.

Bone
Gaucher disease is one of the most common lysosomal storage disorders. Osteonecrosis is a principal clinical manifestation of Gaucher disease and often leads to joint collapse and fractures. T1-weighted (T1w) modality in MRI is widely used to monitor...

Individual and team profiling to support theory of mind in artificial social intelligence.

Scientific reports
We describe an approach aimed at helping artificial intelligence develop theory of mind of their human teammates to support team interactions. We show how this can be supported through the provision of quantifiable, machine-readable, a priori informa...

Utilizing machine learning algorithms for precise discrimination of glycosuria in fluorescence spectroscopic data.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Fluorescence spectroscopy coupled with a random forest machine learning algorithm offers a promising non-invasive approach for diagnosing glycosuria, a condition characterized by excess sugar in the urine of diabetic patients. This study investigated...

Spiking generative adversarial network with attention scoring decoding.

Neural networks : the official journal of the International Neural Network Society
Generative models based on neural networks present a substantial challenge within deep learning. As it stands, such models are primarily limited to the domain of artificial neural networks. Spiking neural networks, as the third generation of neural n...

A syntactic evidence network model for fact verification.

Neural networks : the official journal of the International Neural Network Society
In natural language processing, fact verification is a very challenging task, which requires retrieving multiple evidence sentences from a reliable corpus to verify the authenticity of a claim. Although most of the current deep learning methods use t...

Automatic Recognition of Auditory Brainstem Response Waveforms Using a Deep Learning-Based Framework.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: Recognition of auditory brainstem response (ABR) waveforms may be challenging, particularly for older individuals or those with hearing loss. This study aimed to investigate deep learning frameworks to improve the automatic recognition of ...

A knowledge-enhanced interpretable network for early recurrence prediction of hepatocellular carcinoma via multi-phase CT imaging.

International journal of medical informatics
BACKGROUND: Predicting early recurrence (ER) of hepatocellular carcinoma (HCC) accurately can guide treatment decisions and further enhance survival. Computed tomography (CT) imaging, analyzed by deep learning (DL) models combining domain knowledge, ...