AI Medical Compendium Topic

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

Time

Showing 71 to 80 of 97 articles

Clear Filters

Memory and betweenness preference in temporal networks induced from time series.

Scientific reports
We construct temporal networks from time series via unfolding the temporal information into an additional topological dimension of the networks. Thus, we are able to introduce memory entropy analysis to unravel the memory effect within the considered...

Temporal detection and analysis of guideline interactions.

Artificial intelligence in medicine
BACKGROUND: Clinical practice guidelines (CPGs) are assuming a major role in the medical area, to grant the quality of medical assistance, supporting physicians with evidence-based information of interventions in the treatment of single pathologies. ...

Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting.

PloS one
Time series forecasting has gained much attention due to its many practical applications. Higher-order neural network with recurrent feedback is a powerful technique that has been used successfully for time series forecasting. It maintains fast learn...

Finite-time synchronization of uncertain coupled switched neural networks under asynchronous switching.

Neural networks : the official journal of the International Neural Network Society
This paper deals with the finite-time synchronization problem for a class of uncertain coupled switched neural networks under asynchronous switching. By constructing appropriate Lyapunov-like functionals and using the average dwell time technique, so...

Stability analysis for uncertain switched neural networks with time-varying delay.

Neural networks : the official journal of the International Neural Network Society
In this paper, stability for a class of uncertain switched neural networks with time-varying delay is investigated. By exploring the mode-dependent properties of each subsystem, all the subsystems are categorized into stable and unstable ones. Based ...

Relating observability and compressed sensing of time-varying signals in recurrent linear networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, we study how the dynamics of recurrent networks, formulated as general dynamical systems, mediate the recovery of sparse, time-varying signals. Our formulation resembles the well-described problem of compressed sensing, but in a dynami...

Temporal data representation, normalization, extraction, and reasoning: A review from clinical domain.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: We live our lives by the calendar and the clock, but time is also an abstraction, even an illusion. The sense of time can be both domain-specific and complex, and is often left implicit, requiring significant domain knowledg...

ZeitZeiger: supervised learning for high-dimensional data from an oscillatory system.

Nucleic acids research
Numerous biological systems oscillate over time or space. Despite these oscillators' importance, data from an oscillatory system is problematic for existing methods of regularized supervised learning. We present ZeitZeiger, a method to predict a peri...

Analysis of global O(t(-α)) stability and global asymptotical periodicity for a class of fractional-order complex-valued neural networks with time varying delays.

Neural networks : the official journal of the International Neural Network Society
In this paper, the problem of the global O(t(-α)) stability and global asymptotic periodicity for a class of fractional-order complex-valued neural networks (FCVNNs) with time varying delays is investigated. By constructing suitable Lyapunov function...

Finite-time robust stabilization of uncertain delayed neural networks with discontinuous activations via delayed feedback control.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the finite-time robust stabilization of delayed neural networks (DNNs) in the presence of discontinuous activations and parameter uncertainties. By using the nonsmooth analysis and control theory, a delayed controller is ...