Results 51 to 60 of about 273,096 (313)
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Emerging evidence suggests that low‐frequency neural oscillations are dynamically regulated by consciousness levels, with the recovery of low cortical activity potentially serving as a neurophysiological substrate for conscious emergence. Targeted enhancement of these low‐frequency rhythms in patients with disorders of consciousness
Chuan Xu +10 more
wiley +1 more source
Multidimensional Profiling of MRI‐Negative Temporal Lobe Epilepsy Uncovers Distinct Phenotypes
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Although hippocampal sclerosis (TLE‐HS) represents the most frequent cause of temporal lobe epilepsy (TLE), up to 30% of patients show no lesion on visual MRI inspection (TLE‐MRIneg). These cases pose diagnostic and therapeutic challenges and are underrepresented in surgical series.
Alice Ballerini +28 more
wiley +1 more source
Convolutional Neural Networks Applied to the Performance of a Coffee Tree [PDF]
E3S Web of ConferencesThe use of artificial neural networks has been a significant advancement in the field of computer science, as it supports various fields of study in many traditional sciences. Over the years, numerous models of artificial neural networks have been tested,
Oscar Sánchez Tinoco +2 more
doaj +1 more source
STOCK CLOSING PRICE PREDICTION OF ISX-LISTED INDUSTRIAL COMPANIES USING ARTIFICIAL NEURAL NETWORKS
Jurnal Ilmu Keuangan dan Perbankan, 2022 Making stock investment decisions is a complex challenge that investors continuously face. When it comes to an uncertain future, making the wrong decision can result in massive losses.
Salim Sallal Al-Hasnawi +1 more
doaj +1 more source
Integration of knowledge-based system, artificial neural networks and multimedia for gear design
, 2000 Design is a complicated area consisting of a combination of rules, technical information and personal judgement. The quality of design depends highly on the designer's knowledge and experience.
K Jambunathan +5 more
core +1 more source
Optimal Artificial Neural Network Type Selection Method for Usage in Smart House Systems
Sensors, 2020 In the process of the “smart” house systems work, there is a need to process fuzzy input data. The models based on the artificial neural networks are used to process fuzzy input data from the sensors. However, each artificial neural network has a certain
Vasyl Teslyuk +3 more
doaj +1 more source
On the relationship between predictive coding and backpropagation.
PLoS ONE, 2022 Artificial neural networks are often interpreted as abstract models of biological neuronal networks, but they are typically trained using the biologically unrealistic backpropagation algorithm and its variants.
Robert Rosenbaum
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective We aim to comprehensively analyze how regional tumor and edema characteristics are associated with clinical presentations and survival outcomes in a large cohort of glioblastoma patients. Methods Patients with IDH‐wildtype glioblastoma who received brain MRI from 2010 to 2023 were included.
Daniel J. Zhou +16 more
wiley +1 more source
Concept transfer of synaptic diversity from biological to artificial neural networks
Nature CommunicationsRecent developments in artificial neural networks have drawn inspiration from biological neural networks, leveraging the concept of the artificial neuron to model the learning abilities of biological nerve cells.
Martin Hofmann +3 more
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Digital technologies hold promise for transforming healthcare by enhancing personalized treatments and offer valuable opportunities to improve patient care. Here, we evaluated several novel, self‐administered, home‐based, digital endpoints for their association with corresponding conventional standard clinical measures (primary) in ...
Arne Mueller +14 more
wiley +1 more source