Pages that link to "Item:Q2021272"
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The following pages link to Image-based modelling for adolescent idiopathic scoliosis: mechanistic machine learning analysis and prediction (Q2021272):
Displaying 9 items.
- Unsupervised scoliosis diagnosis via a joint recognition method with multifeature descriptors and centroids extraction (Q1634238) (← links)
- An automatic measurement method of spinal curvature on ultrasound coronal images in adolescent idiopathic scoliosis (Q2045720) (← links)
- Cobb angle measurement of spine from X-ray images using convolutional neural network (Q2632302) (← links)
- Coupled and uncoupled dynamic mode decomposition in multi-compartmental systems with applications to epidemiological and additive manufacturing problems (Q2670383) (← links)
- AI in computational mechanics and engineering sciences (Q2693415) (← links)
- Using image processing techniques in computational mechanics (Q2697790) (← links)
- Patient-specific computational biomechanics for simulating adolescent scoliosis surgery: Predicted vs clinical correction for a preliminary series of six patients (Q3083823) (← links)
- Variational model of scoliosis (Q4986167) (← links)
- Machine learning meta-models for fast parameter identification of the lattice discrete particle model (Q6164296) (← links)
