AIMC Topic: Humans

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Diagnostic value of a vision-based intelligent gait analyzer in screening for gait abnormalities.

Gait & posture
BACKGROUND: Early detection of gait abnormalities is critical for preventing severe injuries in future falls. The timed up and go (TUG) test is a commonly used clinical gait screening test; however, the interpretation of its results is limited to the...

Radiomics in breast MRI: current progress toward clinical application in the era of artificial intelligence.

La Radiologia medica
Breast magnetic resonance imaging (MRI) is the most sensitive imaging modality for breast cancer diagnosis and is widely used clinically. Dynamic contrast-enhanced MRI is the basis for breast MRI, but ultrafast images, T2-weighted images, and diffusi...

Deep Learning for Prediction of N2 Metastasis and Survival for Clinical Stage I Non-Small Cell Lung Cancer.

Radiology
Background Preoperative mediastinal staging is crucial for the optimal management of clinical stage I non-small cell lung cancer (NSCLC). Purpose To develop a deep learning signature for N2 metastasis prediction and prognosis stratification in clinic...

An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research.

Korean journal of radiology
Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by s...

Artificial-intelligence-driven discovery of prognostic biomarker for sarcopenia.

Journal of cachexia, sarcopenia and muscle
BACKGROUND: Sarcopenia is defined as muscle wasting, characterized by a progressive loss of muscle mass and function due to ageing. Diagnosis of sarcopenia typically involves both muscle imaging and the physical performance of people exhibiting signs...

Real-time 3D motion estimation from undersampled MRI using multi-resolution neural networks.

Medical physics
PURPOSE: To enable real-time adaptive magnetic resonance imaging-guided radiotherapy (MRIgRT) by obtaining time-resolved three-dimensional (3D) deformation vector fields (DVFs) with high spatiotemporal resolution and low latency (  ms). Theory and M...

The Route of Motor Recovery in Stroke Patients Driven by Exoskeleton-Robot-Assisted Therapy: A Path-Analysis.

Medical sciences (Basel, Switzerland)
: Exoskeleton-robot-assisted therapy is known to positively affect the recovery of arm functions in stroke patients. However, there is a lack of evidence regarding which variables might favor a better outcome and how this can be modulated by other fa...

Artificial Neural Network Algorithms to Predict Resting Energy Expenditure in Critically Ill Children.

Nutrients
INTRODUCTION: Accurate assessment of resting energy expenditure (REE) can guide optimal nutritional prescription in critically ill children. Indirect calorimetry (IC) is the gold standard for REE measurement, but its use is limited. Alternatively, RE...