Results 51 to 60 of about 874,187 (329)
From omics to AI—mapping the pathogenic pathways in type 2 diabetes
FEBS Letters, EarlyView.Integrating multi‐omics data with AI‐based modelling (unsupervised and supervised machine learning) identify optimal patient clusters, informing AI‐driven accurate risk stratification. Digital twins simulate individual trajectories in real time, guiding precision medicine by matching patients to targeted therapies.
Siobhán O'Sullivan +2 more
wiley +1 more source
Development of neural network model of disc brake operation [PDF]
FME Transactions, 2010 The quality of artificial neural network models mostly depends on a proper setting of neural network architecture i.e. learning algorithm, transfer functions, range and distribution of data used for training, validation, and testing, etc.
Ćirović Velimir, Aleksendrić Dragan
doaj
A Hardware Implementation of Artificial Neural Network Using Field Programmable Gate Arrays [PDF]
, 2007 An artificial neural network algorithm is implemented using a field programmable gate array hardware. One hidden layer is used in the feed-forward neural network structure in order to discriminate one class of patterns from the other class in real time ...
Badala +10 more
core +2 more sources
Decrypting cancer's spatial code: from single cells to tissue niches
Molecular Oncology, EarlyView.Spatial transcriptomics maps gene activity across tissues, offering powerful insights into how cancer cells are organised, switch states and interact with their surroundings. This review outlines emerging computational, artificial intelligence (AI) and geospatial approaches to define cell states, uncover tumour niches and integrate spatial data with ...
Cenk Celik +4 more
wiley +1 more source
New Journal of Physics, 2020 We construct an artificial neural network to study the pairing symmetries in disordered superconductors. For Hamiltonians on square lattice with s-wave, d-wave, and nematic pairing potentials, we use the spin-polarized local density of states near a ...
Liang Chen +3 more
doaj +1 more source
Gating Artificial Neural Network Based Soft Sensor [PDF]
, 2008 This work proposes a novel approach to Soft Sensor modelling, where the Soft Sensor is built by a set of experts which are artificial neural networks with randomly generated topology.
Gabrys, Bogdan, Kadlec, Petr
core
ICU‐EEG Pattern Detection by a Convolutional Neural Network
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Patients in the intensive care unit (ICU) often require continuous EEG (cEEG) monitoring due to the high risk of seizures and rhythmic and periodic patterns (RPPs). However, interpreting cEEG in real time is resource‐intensive and heavily relies on specialized expertise, which is not always available.
Giulio Degano +5 more
wiley +1 more source
Implementing artificial neural networks through bionic construction.
PLoS ONE, 2019 It is evident through biology research that, biological neural network could be implemented through two means: by congenital heredity, or by posteriority learning.
Hu He +9 more
doaj +1 more source
Artificial neural networks in geospatial analysis [PDF]
, 2017 Artificial neural networks are computational models widely used in geospatial analysis for data classification, change detection, clustering, function approximation, and forecasting or prediction. There are many types of neural networks based on learning
Bishop, Carpenter, Carpenter, Ripley
core +1 more source
Exosome Proteomics of SOD1D90A Mutation Suggest Early Disease Mechanisms, and FN1 as a Biomarker
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Amyotrophic lateral sclerosis (ALS) is a neuromuscular disease. Super oxide dismutase 1 (SOD1) gene mutations cause ALS, and the D90A mutation is associated with primarily upper motor neuron (UMN) loss. Objective Our goal is to reveal the early cellular events in ALS pathology and identify potential pharmacokinetic biomarkers, using well ...
Mukesh Gautam +6 more
wiley +1 more source