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Big Data Analytics and Information Science for Business and Biomedical Applications II
| Big Data Analytics and Information Science for Business and Biomedical Applications II |
| Autore | Ahmed S. Ejaz |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (196 p.) |
| Soggetto topico |
Information technology industries
Computer science |
| Soggetto non controllato |
bandwidth selection
correlation edge-preserving image denoising image sequence jump regression analysis local smoothing nonparametric regression spatio-temporal data linear mixed model ridge estimation pretest and shrinkage estimation multicollinearity asymptotic bias and risk LASSO estimation high-dimensional data big data adaptation dividend estimation options markets weighted least squares online health community social support network analysis cancer functional principal component analysis functional predictor linear mixed-effects model mobile device sparse group regularization wearable device data Bayesian modeling functional regression gestational weight infant birth weight joint modeling longitudinal data maternal weight gain transfer learning deep learning pretrained neural networks chest X-ray images lung diseases causal structure learning consistency FCI algorithm high dimensionality nonparametric testing PC algorithm fMRI functional connectivity brain network Human Connectome Project statistics |
| ISBN | 3-0365-5550-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910637784003321 |
Ahmed S. Ejaz
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Identifying Neuroimaging-Based Markers for Distinguishing Brain Disorders
| Identifying Neuroimaging-Based Markers for Distinguishing Brain Disorders |
| Autore | Du Yuhui |
| Pubbl/distr/stampa | Frontiers Media SA, 2020 |
| Descrizione fisica | 1 electronic resource (288 p.) |
| Soggetto topico |
Science: general issues
Neurosciences |
| Soggetto non controllato |
MRI
EEG brain network biomarkers classification |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557259803321 |
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Du Yuhui
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| Frontiers Media SA, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Information Theory in Neuroscience
| Information Theory in Neuroscience |
| Autore | Piasini Eugenio |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (280 p.) |
| Soggetto non controllato |
synergy
Gibbs measures categorical perception entorhinal cortex neural network perceived similarity graph theoretical analysis orderness navigation network eigen-entropy Ising model higher-order correlations discrimination information theory recursion goodness consciousness neuroscience feedforward networks spike train statistics decoding eigenvector centrality discrete Markov chains submodularity free-energy principle infomax principle neural information propagation integrated information mismatched decoding maximum entropy principle perceptual magnet graph theory internal model hypothesis channel capacity complex networks representation latching noise correlations independent component analysis mutual information decomposition connectome redundancy mutual information information entropy production unconscious inference hippocampus neural population coding spike-time precision neural coding maximum entropy neural code Potts model pulse-gating functional connectome integrated information theory minimum information partition brain network Queyranne’s algorithm principal component analysis |
| ISBN | 3-03897-665-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346856603321 |
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Piasini Eugenio
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Radiolabelled Molecules for Brain Imaging with PET and SPECT
| Radiolabelled Molecules for Brain Imaging with PET and SPECT |
| Autore | Brust Peter |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (244 p.) |
| Soggetto topico |
Research & information: general
Biology, life sciences |
| Soggetto non controllato |
SV2A
SV2B SV2C microPET [18F]UCB-H epilepsy PBIF distribution volume blocking assay preclinical imaging Alzheimer’s disease (AD) network measure graph theory brain network positron emission tomography (PET) persistent homology Phosphodiesterase 2A (PDE2A) Positron Emission Tomography (PET) Benzoimidazotriazine (BIT) fluorinated Mouse Liver Microsomes (MLM) cyclic nucleotide phosphodiesterase PDE2A radioligand nitro-precursor fluorine-18 in vitro autoradiography PET imaging opioid receptors positron emission tomography radiotracers μOR-, δOR-, κOR- and ORL1-ligands movement disorders pain drug dependence GBM biomarkers Sigma 1 Sigma 2 PD-L1 PARP IDH Alzheimer’s disease Parkinson’s disease β-amyloid plaques neurofibrillary tangles α-synucleinopathy diagnostic imaging probes orexin receptors PET radiotracer imaging alpha 7 nicotinic acetylcholine receptors nAChR autoradiography amino acid FET FACBC FDOPA immunoPET molecular imaging glioma brain metastases adenosine A2A receptor rotenone-based mouse model [18F]FESCH two-step one-pot radiosynthesis |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557295103321 |
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Brust Peter
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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