Results 111 to 120 of about 2,212,722 (355)

Precision‐Optimised Post‐Stroke Prognoses

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Current medicine cannot confidently predict who will recover from post‐stroke impairments. Researchers have sought to bridge this gap by treating the post‐stroke prognostic problem as a machine learning problem, reporting prediction error metrics across samples of patients whose outcomes are known.
Thomas M. H. Hope, Howard Bowman, Rachel M. Bruce, Alex P. Leff, Cathy J. Price   +4 more
wiley   +1 more source

The free recall search process introduces errors in short term memory but apparently not in long term memory [PDF]

, 2011
Here it is reported that the free recall search process increases the error rate for short term memory (about 1% per second in data from Murdock & Okada (1970)) but not for long term memory (in data from McDermott (1996)).
Tarnow, Dr. Eugen
core  

Simulation and Empirical Studies of Long Short-Term Memory Performance to Deal with Limited Data

JOIN: Jurnal Online Informatika
This research is proposed to determine the performance of time series machine learning in the presence of noise, where this approach is intended to forecast time series data.
Khusnia Nurul Khikmah, Kusman Sadik, Khairil Anwar Notodiputro   +2 more
doaj   +1 more source

Neuropsin‐dependent and ‐independent behavioral tagging

Neuropsychopharmacology Reports, 2021
Aim The consolidation of short‐term memories into long‐term memories is promoted by associations with novel environmental stimuli. This phenomenon is known as behavioral tagging.
Yuka Suzuki, Yuya Yoda, Yasuyuki Ishikawa   +2 more
doaj   +1 more source

Plasma microRNA Signature as Predictive Marker of Clinical Response to Therapy During Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Despite the availability of effective therapies for Multiple Sclerosis (MS), the unpredictable nature of disease progression and the variability in individual treatment outcomes call for reliable biomarkers. This pilot study aims to investigate the potential of plasma circulating microRNAs (miRNAs) as predictive biomarkers for ...
Fortunata Carbone, Alessandra Colamatteo, Teresa Micillo, Gianmarco Abbadessa, Silvia Garavelli, Clorinda Fusco, Claudia Russo, Francesco Perna, Federica Garziano, Claudia La Rocca, Maria Mottola, Giorgia Teresa Maniscalco, Simona Bonavita, Antonio Luca Spiezia, Alessia Castiello, Roberta Lanzillo, Vincenzo Brescia Morra, Claudio Procaccini, Paola de Candia, Giuseppe Matarese   +19 more
wiley   +1 more source

Long Short-Term Memory Neuron Equalizer

, 2020
In this work we propose a neuromorphic hardware based signal equalizer by based on the deep learning implementation. The proposed neural equalizer is plasticity trainable equalizer which is different from traditional model designed based DFE. A trainable Long Short-Term memory neural network based DFE architecture is proposed for signal recovering and ...
Wang, Zihao, Xu, Zhifei, He, Jiayi, Hwang, Chulsoon, Fan, Jun, Delingette, Hervé   +5 more
openaire   +2 more sources

Data‐driven forecasting of ship motions in waves using machine learning and dynamic mode decomposition

International Journal of Adaptive Control and Signal Processing, EarlyView.
Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez, Mauro Gaggero, Andrea Serani   +2 more
wiley   +1 more source

Long Short Term Memory on Chronic Laryngitis Classification

Procedia Computer Science, 2018
Abstract The classification study with the use of machine learning concepts has been applied for years, and one of the aspects in which this can be applied is for the analysis of speech acoustics applied to the analysis of pathologies. Among the pathologies present, one of them is chronic laryngitis. Thus, this article aims to present the results for
Guedes, Victor, Candido Junior, Arnaldo, Fernandes, Joana Filipa Teixeira, Teixeira, Felipe, Teixeira, João Paulo   +4 more
openaire   +3 more sources

Neural Network Adaptive Control With Long Short‐Term Memory

International Journal of Adaptive Control and Signal Processing, EarlyView.
ABSTRACT In this study, we propose a novel adaptive control architecture that provides dramatically better transient response performance compared to conventional adaptive control methods. This is accomplished by the synergistic employment of a traditional adaptive neural network (ANN) controller and a long short‐term memory (LSTM) network.
Emirhan Inanc, Abdullah Habboush, Yigit Gurses, Yildiray Yildiz, Anuradha M. Annaswamy   +4 more
wiley   +1 more source

Short-Term Plasticity and Long-Term Potentiation in Magnetic Tunnel Junctions: Towards Volatile Synapses

, 2016
Synaptic memory is considered to be the main element responsible for learning and cognition in humans. Although traditionally non-volatile long-term plasticity changes have been implemented in nanoelectronic synapses for neuromorphic applications, recent
Roy, Kaushik, Sengupta, Abhronil
core   +1 more source