AIMC Topic:
Computer Simulation

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Machine learning methods for leveraging baseline covariate information to improve the efficiency of clinical trials.

Statistics in medicine
Clinical trials are widely considered the gold standard for treatment evaluation, and they can be highly expensive in terms of time and money. The efficiency of clinical trials can be improved by incorporating information from baseline covariates tha...

Avian-inspired energy-harvesting from atmospheric phenomena for small UAVs.

Bioinspiration & biomimetics
Fixed-wing small, unmanned aerial vehicles usually fly in atmospheric boundary layers that are often under the influence of turbulent environments. Inspired by nature's flyers, an application of an energy-harvesting flight strategy for increasing the...

Spontaneous activity emerging from an inferred network model captures complex spatio-temporal dynamics of spike data.

Scientific reports
Inference methods are widely used to recover effective models from observed data. However, few studies attempted to investigate the dynamics of inferred models in neuroscience, and none, to our knowledge, at the network level. We introduce a principl...

Neural network modelling of soft tissue deformation for surgical simulation.

Artificial intelligence in medicine
This paper presents a new neural network methodology for modelling of soft tissue deformation for surgical simulation. The proposed methodology formulates soft tissue deformation and its dynamics as the neural propagation and dynamics of cellular neu...

Multistability of Switched Neural Networks With Piecewise Linear Activation Functions Under State-Dependent Switching.

IEEE transactions on neural networks and learning systems
This paper is concerned with the multistability of switched neural networks with piecewise linear activation functions under state-dependent switching. Under some reasonable assumptions on the switching threshold and activation functions, by using th...

Fully tuned RBF neural network controller for ultrasound hyperthermia cancer tumour therapy.

Network (Bristol, England)
Thermal dose is an important clinical efficacy index for hyperthermia cancer treatment. This paper presents a new direct radial basis function (RBF) neural network controller for high-temperature hyperthermia thermal dose during the therapeutic proce...

Data-Driven Elasticity Imaging Using Cartesian Neural Network Constitutive Models and the Autoprogressive Method.

IEEE transactions on medical imaging
Quasi-static elasticity imaging techniques rely on model-based mathematical inverse methods to estimate mechanical parameters from force-displacement measurements. These techniques introduce simplifying assumptions that preclude exploration of unknow...

A deep learning approach to automate refinement of somatic variant calling from cancer sequencing data.

Nature genetics
Cancer genomic analysis requires accurate identification of somatic variants in sequencing data. Manual review to refine somatic variant calls is required as a final step after automated processing. However, manual variant refinement is time-consumin...

Generalized multifactor dimensionality reduction approaches to identification of genetic interactions underlying ordinal traits.

Genetic epidemiology
The manifestation of complex traits is influenced by gene-gene and gene-environment interactions, and the identification of multifactor interactions is an important but challenging undertaking for genetic studies. Many complex phenotypes such as dise...

Hybrid PSO-FLC for dynamic global peak extraction of the partially shaded photovoltaic system.

PloS one
Particle Swarm Optimization (PSO) is widely used in maximum power point tracking (MPPT) of photovoltaic (PV) energy systems. Nevertheless, this technique suffers from two main problems in the case of partial shading conditions (PSCs). The first probl...