AIMC Topic: Adult

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Learning a Hand Model From Dynamic Movements Using High-Density EMG and Convolutional Neural Networks.

IEEE transactions on bio-medical engineering
OBJECTIVE: Surface electromyography (sEMG) can sense the motor commands transmitted to the muscles. This work presents a deep learning method that can decode the electrophysiological activity of the forearm muscles into the movements of the human han...

A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development.

IEEE transactions on bio-medical engineering
OBJECTIVE: Brain dynamic effective connectivity (dEC), characterizes the information transmission patterns between brain regions that change over time, which provides insight into the biological mechanism underlying brain development. However, most e...

Artificial intelligence contouring in radiotherapy for organs-at-risk and lymph node areas.

Radiation oncology (London, England)
INTRODUCTION: The delineation of organs-at-risk and lymph node areas is a crucial step in radiotherapy, but it is time-consuming and associated with substantial user-dependent variability in contouring. Artificial intelligence (AI) appears to be the ...

A machine learning model revealed that exosome small RNAs may participate in the development of breast cancer through the chemokine signaling pathway.

BMC cancer
BACKGROUND: Exosome small RNAs are believed to be involved in the pathogenesis of cancer, but their role in breast cancer is still unclear. This study utilized machine learning models to screen for key exosome small RNAs and analyzed and validated th...

Preferences for attributes of an artificial intelligence-based risk assessment tool for HIV and sexually transmitted infections: a discrete choice experiment.

BMC public health
INTRODUCTION: Early detection and treatment of HIV and sexually transmitted infections (STIs) are crucial for effective control. We previously developed MySTIRisk, an artificial intelligence-based risk tool that predicts the risk of HIV and STIs. We ...

Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models.

BMC psychiatry
BACKGROUND: Suicidal behaviors, which may lead to death (suicide) or survival (suicide attempt), are influenced by various factors. Identifying the specific risk factors for suicidal behavior mortality is critical for improving prevention strategies ...

The diagnostic value of MRI segmentation technique for shoulder joint injuries based on deep learning.

Scientific reports
This work is to investigate the diagnostic value of a deep learning-based magnetic resonance imaging (MRI) image segmentation (IS) technique for shoulder joint injuries (SJIs) in swimmers. A novel multi-scale feature fusion network (MSFFN) is develop...

A digital phenotyping dataset for impending panic symptoms: a prospective longitudinal study.

Scientific data
This study investigated the utilization of digital phenotypes and machine learning algorithms to predict impending panic symptoms in patients with mood and anxiety disorders. A cohort of 43 patients was monitored over a two-year period, with data col...

The Promise of AI for Image-Driven Medicine: Qualitative Interview Study of Radiologists' and Pathologists' Perspectives.

JMIR human factors
BACKGROUND: Image-driven specialisms such as radiology and pathology are at the forefront of medical artificial intelligence (AI) innovation. Many believe that AI will lead to significant shifts in professional roles, so it is vital to investigate ho...

Assessment of non-fatal injuries among university students in Hainan: a machine learning approach to exploring key factors.

Frontiers in public health
BACKGROUND: Injuries constitute a significant global public health concern, particularly among individuals aged 0-34. These injuries are affected by various social, psychological, and physiological factors and are no longer viewed merely as accidenta...