AI Medical Compendium Topic

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A robust transfer learning approach for high-dimensional linear regression to support integration of multi-source gene expression data.

PLoS computational biology
Transfer learning aims to integrate useful information from multi-source datasets to improve the learning performance of target data. This can be effectively applied in genomics when we learn the gene associations in a target tissue, and data from ot...

ARGai 1.0: A GAN augmented in silico approach for identifying resistant genes and strains in E. coli using vision transformer.

Computational biology and chemistry
The emergence of infectious disease and antibiotic resistance in bacteria like Escherichia coli (E. coli) shows the necessity for novel computational techniques for identifying essential genes that contribute to resistance. The task of identifying re...

Research on boundary control of vehicle-mounted flexible manipulator based on partial differential equations.

PloS one
Vehicle-mounted flexible robotic arms (VFRAs) are crucial in enhancing operational capabilities in sectors where human intervention is limited due to accessibility or safety concerns, such as hazardous environments or precision surgery. This paper in...

Situation-Based Neuromorphic Memory in Spiking Neuron-Astrocyte Network.

IEEE transactions on neural networks and learning systems
Mammalian brains operate in very special surroundings: to survive they have to react quickly and effectively to the pool of stimuli patterns previously recognized as danger. Many learning tasks often encountered by living organisms involve a specific...

Machine learning models based on FEM simulation of hoop mode vibrations to enable ultrasonic cuffless measurement of blood pressure.

Medical & biological engineering & computing
Blood pressure (BP) is one of the vital physiological parameters, and its measurement is done routinely for almost all patients who visit hospitals. Cuffless BP measurement has been of great research interest over the last few years. In this paper, w...

A smooth gradient approximation neural network for general constrained nonsmooth nonconvex optimization problems.

Neural networks : the official journal of the International Neural Network Society
Nonsmooth nonconvex optimization problems are pivotal in engineering practice due to the inherent nonsmooth and nonconvex characteristics of many real-world complex systems and models. The nonsmoothness and nonconvexity of the objective and constrain...

Machine learning and statistical shape modelling for real-time prediction of stent deployment in realistic anatomies.

Computer methods and programs in biomedicine
The rise in minimally invasive procedures has created a demand for efficient and reliable planning software to predict intra- and post-operative outcomes. Surrogate modelling has shown promise, but challenges remain, particularly in cardiovascular ap...

Convergence analysis of deep Ritz method with over-parameterization.

Neural networks : the official journal of the International Neural Network Society
The deep Ritz method (DRM) has recently been shown to be a simple and effective method for solving PDEs. However, the numerical analysis of DRM is still incomplete, especially why over-parameterized DRM works remains unknown. This paper presents the ...

Machine Learning-Enhanced Predictive Modeling for Arbitrary Deterministic Lateral Displacement Design and Test.

IEEE transactions on nanobioscience
The separation of biological particles like cells and macromolecules from liquid samples is vital in clinical medicine, supporting liquid biopsies and diagnostics. Deterministic Lateral Displacement (DLD) is prominent for sorting particles in microfl...

Finite-time H output synchronization for DCRDNNs with multiple delayed and adaptive output couplings.

Neural networks : the official journal of the International Neural Network Society
This work concentrates on solving the finite-time H output synchronization (FTHOS) issue of directed coupled reaction-diffusion neural networks (DCRDNNs) with multiple delayed and adaptive output couplings in the presence of external disturbances. Ba...