AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Motion

Showing 181 to 190 of 845 articles

Clear Filters

Improving BLE-Based Passive Human Sensing with Deep Learning.

Sensors (Basel, Switzerland)
Passive Human Sensing (PHS) is an approach to collecting data on human presence, motion or activities that does not require the sensed human to carry devices or participate actively in the sensing process. In the literature, PHS is generally performe...

: Quantification of user-defined animal behaviors using learning-based holistic assessment.

Cell reports methods
Quantifying animal behavior is important for biological research. Identifying behaviors is the prerequisite of quantifying them. Current computational tools for behavioral quantification typically use high-level properties such as body poses to ident...

Development of a Real-Time 6-DOF Motion-Tracking System for Robotic Computer-Assisted Implant Surgery.

Sensors (Basel, Switzerland)
In this paper, we investigate a motion-tracking system for robotic computer-assisted implant surgery. Failure of the accurate implant positioning may result in significant problems, thus an accurate real-time motion-tracking system is crucial for avo...

Muscular Damping Distribution Strategy for Bio-Inspired, Soft Motion Control at Variable Precision.

Sensors (Basel, Switzerland)
Bio-inspired and compliant control approaches have been studied by roboticists for decades to achieve more natural robot motion. Independent of this, medical and biological researchers have discovered a wide variety of muscular properties and higher-...

Evaluation of real-time tumor contour prediction using LSTM networks for MR-guided radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Magnetic resonance imaging guided radiotherapy (MRgRT) with deformable multileaf collimator (MLC) tracking would allow to tackle both rigid displacement and tumor deformation without prolonging treatment. However, the system l...

Design and Performance Verification of a Novel RCM Mechanism for a Minimally Invasive Surgical Robot.

Sensors (Basel, Switzerland)
Minimally invasive surgical robots have the advantages of high positioning accuracy, good stability, and flexible operation, which can effectively improve the quality of surgery and reduce the difficulty for doctors to operate. However, in order to r...

LGEANet: LSTM-global temporal convolution-external attention network for respiratory motion prediction.

Medical physics
PURPOSE: To develop a deep learning network that treats the three-dimensional respiratory motion signals as a whole and considers the inter-dimensional correlation between signals of different directions for accurate respiratory tumor motion predicti...

Motion compensated self supervised deep learning for highly accelerated 3D ultrashort Echo time pulmonary MRI.

Magnetic resonance in medicine
PURPOSE: To investigate motion compensated, self-supervised, model based deep learning (MBDL) as a method to reconstruct free breathing, 3D pulmonary UTE acquisitions.

Simulation-based inference for non-parametric statistical comparison of biomolecule dynamics.

PLoS computational biology
Numerous models have been developed to account for the complex properties of the random walks of biomolecules. However, when analysing experimental data, conditions are rarely met to ensure model identification. The dynamics may simultaneously be inf...

A feedforward unitary equivariant neural network.

Neural networks : the official journal of the International Neural Network Society
We devise a new type of feedforward neural network. It is equivariant with respect to the unitary group U(n). The input and output can be vectors in ℂ with arbitrary dimension n. No convolution layer is required in our implementation. We avoid errors...