AIMC Topic: Time Factors

Clear Filters Showing 391 to 400 of 2001 articles

Timing matters for accurate identification of the epileptogenic zone.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Interictal biomarkers of the epileptogenic zone (EZ) and their use in machine learning models open promising avenues for improvement of epilepsy surgery evaluation. Currently, most studies restrict their analysis to short segments of intra...

Methodology based on spiking neural networks for univariate time-series forecasting.

Neural networks : the official journal of the International Neural Network Society
Spiking Neural Networks (SNN) are recognised as well-suited for processing spatiotemporal information with ultra-low energy consumption. However, proposals based on SNN for classification tasks are more common than for forecasting problems. In this s...

Exploring Transformer Model in Longitudinal Pharmacokinetic/Pharmacodynamic Analyses and Comparing with Alternative Natural Language Processing Models.

Journal of pharmaceutical sciences
There remains a substantial need for a comprehensive assessment of various natural language processing (NLP) algorithms in longitudinal pharmacokinetic/pharmacodynamic (PK/PD) modeling despite recent advances in machine learning in the space of quant...

Quasi-synchronization for variable-order fractional complex dynamical networks with hybrid delay-dependent impulses.

Neural networks : the official journal of the International Neural Network Society
This paper focuses on addressing the problem of quasi-synchronization in heterogeneous variable-order fractional complex dynamical networks (VFCDNs) with hybrid delay-dependent impulses. Firstly, a mathematics model of VFCDNs with short memory is est...

Bayesian hypernetwork collaborates with time-difference evolutional network for temporal knowledge prediction.

Neural networks : the official journal of the International Neural Network Society
A Temporal Knowledge Graph (TKG) is a sequence of Knowledge Graphs (KGs) attached with time information, in which each KG contains the facts that co-occur at the same timestamp. Temporal knowledge prediction (TKP) aims to predict future events given ...

Rapid and accurate identification of marine bacteria spores at a single-cell resolution by laser tweezers Raman spectroscopy and deep learning.

Journal of biophotonics
Marine bacteria have been considered as important participants in revealing various carbon/sulfur/nitrogen cycles of marine ecosystem. Thus, how to accurately identify rare marine bacteria without a culture process is significant and valuable. In thi...

Machine learning models for predicting unscheduled return visits to an emergency department: a scoping review.

BMC emergency medicine
BACKGROUND: Unscheduled return visits (URVs) to emergency departments (EDs) are used to assess the quality of care in EDs. Machine learning (ML) models can incorporate a wide range of complex predictors to identify high-risk patients and reduce error...

Reservoir Computing With Dynamic Reservoir using Cascaded DNA Memristors.

IEEE transactions on biomedical circuits and systems
This article proposes molecular and DNA memristors where the state is defined by a single output variable. In past molecular and DNA memristors, the state of the memristor was defined based on two output variables. These memristors cannot be cascaded...

IMU-Based Fitness Activity Recognition Using CNNs for Time Series Classification.

Sensors (Basel, Switzerland)
Mobile fitness applications provide the opportunity to show users real-time feedback on their current fitness activity. For such applications, it is essential to accurately track the user's current fitness activity using available mobile sensors, suc...