AIMC Topic: Rotation

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Assessing the impact of occlusal plane rotation on facial aesthetics in orthodontic treatment: a machine learning approach.

BMC oral health
BACKGROUND: Adequate occlusal plane (OP) rotation through orthodontic therapy enables satisfying profile improvements for patients who are disturbed by their maxillomandibular imbalance but reluctant to surgery. The study aims to quantify profile imp...

Effect of Retrograde Autologous Priming on Coagulation Assessed by Rotation Thromboelastometry in Patients Undergoing Valvular Cardiac Surgery.

Journal of cardiothoracic and vascular anesthesia
OBJECTIVES: To investigate the effect of retrograde autologous priming (RAP) on coagulation function using rotation thromboelastometry (ROTEM) in patients undergoing valvular cardiac surgery.

Sparse annotation learning for dense volumetric MR image segmentation with uncertainty estimation.

Physics in medicine and biology
Training neural networks for pixel-wise or voxel-wise image segmentation is a challenging task that requires a considerable amount of training samples with highly accurate and densely delineated ground truth maps. This challenge becomes especially pr...

EQNAS: Evolutionary Quantum Neural Architecture Search for Image Classification.

Neural networks : the official journal of the International Neural Network Society
Quantum neural network (QNN) is a neural network model based on the principles of quantum mechanics. The advantages of faster computing speed, higher memory capacity, smaller network size and elimination of catastrophic amnesia make it a new idea to ...

State-of-the-Art of Non-Radiative, Non-Visual Spine Sensing with a Focus on Sensing Forces, Vibrations and Bioelectrical Properties: A Systematic Review.

Sensors (Basel, Switzerland)
In the research field of robotic spine surgery, there is a big upcoming momentum for surgeon-like autonomous behaviour and surgical accuracy in robotics which goes beyond the standard engineering notions such as geometric precision. The objective of ...

Understanding calibration of deep neural networks for medical image classification.

Computer methods and programs in biomedicine
Background and Objective - In the field of medical image analysis, achieving high accuracy is not enough; ensuring well-calibrated predictions is also crucial. Confidence scores of a deep neural network play a pivotal role in explainability by provid...

E(3) equivariant graph neural networks for robust and accurate protein-protein interaction site prediction.

PLoS computational biology
Artificial intelligence-powered protein structure prediction methods have led to a paradigm-shift in computational structural biology, yet contemporary approaches for predicting the interfacial residues (i.e., sites) of protein-protein interaction (P...

Shoulder Range of Motion Measurement Using Inertial Measurement Unit-Validation with a Robot Arm.

Sensors (Basel, Switzerland)
The invention of inertial measurement units allowed the construction of sensors suitable for human motion tracking that are more affordable than expensive optical motion capture systems, but there are a few factors influencing their accuracy, such as...

Protein model quality assessment using rotation-equivariant transformations on point clouds.

Proteins
Machine learning research concerning protein structure has seen a surge in popularity over the last years with promising advances for basic science and drug discovery. Working with macromolecular structure in a machine learning context requires an ad...

Fiber Bundle Image Reconstruction Using Convolutional Neural Networks and Bundle Rotation in Endomicroscopy.

Sensors (Basel, Switzerland)
Fiber-bundle endomicroscopy has several recognized drawbacks, the most prominent being the honeycomb effect. We developed a multi-frame super-resolution algorithm exploiting bundle rotation to extract features and reconstruct underlying tissue. Simul...