AIMC Topic: Humans

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A machine learning approach for vocal fold segmentation and disorder classification based on ensemble method.

Scientific reports
In the healthcare domain, the essential task is to understand and classify diseases affecting the vocal folds (VFs). The accurate identification of VF disease is the key issue in this domain. Integrating VF segmentation and disease classification int...

Hotspots and trends of artificial intelligence in the field of cataracts: a bibliometric analysis.

International ophthalmology
PURPOSE: To analyze the hotspots and trends in artificial intelligence (AI) research in the field of cataracts.

Band power feature part-based convolutional neural network with African vulture optimization fostered channel selection for EEG classification.

Computer methods in biomechanics and biomedical engineering
The electroencephalogram-based motor imagery (MI-EEG) classification task is significant for brain-computer interface (BCI). EEG signals need a lot of channels to be acquired, which makes it difficult to use in real-world applications. Choosing the o...

Evaluation of a Large Language Model's Ability to Assist in an Orthopedic Hand Clinic.

Hand (New York, N.Y.)
BACKGROUND: Advancements in artificial intelligence technology, such as OpenAI's large language model, ChatGPT, could transform medicine through applications in a clinical setting. This study aimed to assess the utility of ChatGPT as a clinical assis...

Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence-review of evidence and proposition of a roadmap to clinical translation.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment of heart disease; however, limitations of CMR include long exam times and high complexity compared to other cardiac imaging modalities. Recently a...

Artificial intelligence in the era of planetary health: insights on its application for the climate change-mental health nexus in the Philippines.

International review of psychiatry (Abingdon, England)
This review explores the transformative potential of Artificial Intelligence (AI) in the light of evolving threats to planetary health, particularly the dangers posed by the climate crisis and its emerging mental health impacts, in the context of a c...

Deep Learning-Enabled Automated Quality Control for Liver MR Elastography: Initial Results.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Several factors can impair image quality and reliability of liver magnetic resonance elastography (MRE), such as inadequate driver positioning, insufficient wave propagation and patient-related factors.

AutoAMS: Automated attention-based multi-modal graph learning architecture search.

Neural networks : the official journal of the International Neural Network Society
Multi-modal attention mechanisms have been successfully used in multi-modal graph learning for various tasks. However, existing attention-based multi-modal graph learning (AMGL) architectures heavily rely on manual design, requiring huge effort and e...

Infinite-dimensional reservoir computing.

Neural networks : the official journal of the International Neural Network Society
Reservoir computing approximation and generalization bounds are proved for a new concept class of input/output systems that extends the so-called generalized Barron functionals to a dynamic context. This new class is characterized by the readouts wit...

Deep learning-based detection of lumbar spinal canal stenosis using convolutional neural networks.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Lumbar spinal canal stenosis (LSCS) is the most common spinal degenerative disorder in elderly people and usually first seen by primary care physicians or orthopedic surgeons who are not spine surgery specialists. Magnetic resonan...