Symbolic algorithm
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- Klíčová slova
- teorie multimediálního uživatelského rozhraní,
- MeSH
- algoritmy MeSH
- Bayesova věta MeSH
- filozofie MeSH
- fyzika metody trendy MeSH
- kognitivní věda metody trendy MeSH
- lidé MeSH
- metafyzické vztahy mezi duší a tělem fyziologie klasifikace MeSH
- mozek fyziologie MeSH
- nervové receptory fyziologie MeSH
- percepce fyziologie klasifikace MeSH
- planetární evoluce MeSH
- rozpoznávání obrazu fyziologie klasifikace MeSH
- sebepojetí * MeSH
- statistika jako téma MeSH
- teorie mysli * fyziologie klasifikace MeSH
- vědomí * fyziologie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- přehledy MeSH
In genetic programming (GP), computer programs are often coevolved with training data subsets that are known as fitness predictors. In order to maximize performance of GP, it is important to find the most suitable parameters of coevolution, particularly the fitness predictor size. This is a very time-consuming process as the predictor size depends on a given application, and many experiments have to be performed to find its suitable size. A new method is proposed which enables us to automatically adapt the predictor and its size for a given problem and thus to reduce not only the time of evolution, but also the time needed to tune the evolutionary algorithm. The method was implemented in the context of Cartesian genetic programming and evaluated using five symbolic regression problems and three image filter design problems. In comparison with three different CGP implementations, the time required by CGP search was reduced while the quality of results remained unaffected.
- MeSH
- algoritmy * MeSH
- biologická evoluce * MeSH
- genetická zdatnost MeSH
- lidé MeSH
- počítačová simulace MeSH
- počítačové zpracování obrazu metody MeSH
- poměr signál - šum MeSH
- regresní analýza MeSH
- software * MeSH
- vylepšení obrazu metody MeSH
- výpočetní biologie metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Research in Artificial Intelligence (AI) has focused mostly on two extremes: either on small improvements in narrow AI domains, or on universal theoretical frameworks which are often uncomputable, or lack practical implementations. In this paper we attempt to follow a big picture view while also providing a particular theory and its implementation to present a novel, purposely simple, and interpretable hierarchical architecture. This architecture incorporates the unsupervised learning of a model of the environment, learning the influence of one's own actions, model-based reinforcement learning, hierarchical planning, and symbolic/sub-symbolic integration in general. The learned model is stored in the form of hierarchical representations which are increasingly more abstract, but can retain details when needed. We demonstrate the universality of the architecture by testing it on a series of diverse environments ranging from audio/visual compression to discrete and continuous action spaces, to learning disentangled representations.
- MeSH
- algoritmy MeSH
- lidé MeSH
- neuronové sítě MeSH
- posilování (psychologie) MeSH
- strojové učení bez učitele MeSH
- učení fyziologie MeSH
- umělá inteligence * MeSH
- životní prostředí * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Boolean networks (BNs) provide an effective modelling formalism for various complex biochemical phenomena. Their long term behaviour is represented by attractors-subsets of the state space towards which the BN eventually converges. These are then typically linked to different biological phenotypes. Depending on various logical parameters, the structure and quality of attractors can undergo a significant change, known as a bifurcation. We present a methodology for analysing bifurcations in asynchronous parametrised Boolean networks. RESULTS: In this paper, we propose a computational framework employing advanced symbolic graph algorithms that enable the analysis of large networks with hundreds of Boolean variables. To visualise the results of this analysis, we developed a novel interactive presentation technique based on decision trees, allowing us to quickly uncover parameters crucial to the changes in the attractor landscape. As a whole, the methodology is implemented in our tool AEON. We evaluate the method's applicability on a complex human cell signalling network describing the activity of type-1 interferons and related molecules interacting with SARS-COV-2 virion. In particular, the analysis focuses on explaining the potential suppressive role of the recently proposed drug molecule GRL0617 on replication of the virus. CONCLUSIONS: The proposed method creates a working analogy to the concept of bifurcation analysis widely used in kinetic modelling to reveal the impact of parameters on the system's stability. The important feature of our tool is its unique capability to work fast with large-scale networks with a relatively large extent of unknown information. The results obtained in the case study are in agreement with the recent biological findings.
- MeSH
- algoritmy MeSH
- aniliny MeSH
- benzamidy MeSH
- COVID-19 * MeSH
- genové regulační sítě * MeSH
- lidé MeSH
- modely genetické MeSH
- naftaleny MeSH
- SARS-CoV-2 MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Text podává základní přehled o indikacích a kontraindikacích neuropsychologického vyšetření zejména v lékařských zařízeních. Popisuje jednotlivé části indikačního procesu a nabízí algoritmus pro orientaci v indikacích neuropsychologického vyšetření od praktického lékaře až po specialisty.
The text aims at introducing the criteria for referral questions regarding neuropsychological assessment in clinical settings. A brief description of different referral questions including separate phases of neuropsychological assessment follows. We provide also an algorithm for choosing the right referral question for general practitioners and specialists as well.
- MeSH
- lidé MeSH
- nemoci nervového systému * diagnóza MeSH
- neuropsychologické testy * MeSH
- Check Tag
- lidé MeSH
Text podává základní přehled o indikacích a kontraindikacích neuropsychologického vyšetření zejména v lékařských zařízeních. Popisuje jednotlivé části indikačního procesu a nabízí algoritmus pro orientaci v indikacích neuropsychologického vyšetření od praktického lékaře až po specialisty.
The text aims at introducing the criteria for referral questions regarding neuropsychological assessment in clinical settings. A brief description of different referral questions including separate phases of neuropsychological assessment follows. We provide also an algorithm for choosing the right referral question for general practitioners and specialists as well.
- MeSH
- lidé MeSH
- nemoci nervového systému * diagnóza MeSH
- neuropsychologické testy * MeSH
- Check Tag
- lidé MeSH
In order to improve the h-index in terms of its accuracy and sensitivity to the form of the citation distribution, we propose the new bibliometric index [symbol in text]. The basic idea is to define, for any author with a given number of citations, an "ideal" citation distribution which represents a benchmark in terms of number of papers and number of citations per publication, and to obtain an index which increases its value when the real citation distribution approaches its ideal form. The method is very general because the ideal distribution can be defined differently according to the main objective of the index. In this paper we propose to define it by a "squared-form" distribution: this is consistent with many popular bibliometric indices, which reach their maximum value when the distribution is basically a "square". This approach generally rewards the more regular and reliable researchers, and it seems to be especially suitable for dealing with common situations such as applications for academic positions. To show the advantages of the [symbol in text]-index some mathematical properties are proved and an application to real data is proposed.
BACKGROUND AND PURPOSE: While impaired cognitive performance is common in multiple sclerosis (MS), it has been largely underdiagnosed. Here a magnetic resonance imaging (MRI) screening algorithm is proposed to identify patients at highest risk of cognitive impairment. The objective was to examine whether assessment of lesion burden together with whole brain atrophy on MRI improves our ability to identify cognitively impaired MS patients. METHODS: Of the 1253 patients enrolled in the study, 1052 patients with all cognitive, volumetric MRI and clinical data available were included in the analysis. Brain MRI and neuropsychological assessment with the Brief International Cognitive Assessment for Multiple Sclerosis were performed. Multivariable logistic regression and individual prediction analysis were used to investigate the associations between MRI markers and cognitive impairment. The results of the primary analysis were validated at two subsequent time points (months 12 and 24). RESULTS: The prevalence of cognitive impairment was greater in patients with low brain parenchymal fraction (BPF) (<0.85) and high T2 lesion volume (T2-LV) (>3.5 ml) than in patients with high BPF (>0.85) and low T2-LV (<3.5 ml), with an odds ratio (OR) of 6.5 (95% CI 4.4-9.5). Low BPF together with high T2-LV identified in 270 (25.7%) patients predicted cognitive impairment with 83% specificity, 82% negative predictive value, 51% sensitivity and 75% overall accuracy. The risk of confirmed cognitive decline over the follow-up was greater in patients with high T2-LV (OR 2.1; 95% CI 1.1-3.8) and low BPF (OR 2.6; 95% CI 1.4-4.7). CONCLUSIONS: The integrated MRI assessment of lesion burden and brain atrophy may improve the stratification of MS patients who may benefit from cognitive assessment.
- MeSH
- atrofie diagnostické zobrazování patologie MeSH
- dospělí MeSH
- kognitivní dysfunkce diagnostické zobrazování patologie psychologie MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonanční tomografie metody MeSH
- mozek diagnostické zobrazování patologie MeSH
- neuropsychologické testy MeSH
- roztroušená skleróza diagnostické zobrazování patologie psychologie MeSH
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- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: The ability to understand emotions is often disturbed in patients with cognitive impairments. Right temporal lobe structures play a crucial role in emotional processing, especially the amygdala, temporal pole (TP), superior temporal sulcus (STS), and anterior cingulate (AC). Those regions are affected in early stages of Alzheimer ́s disease (AD). The aim of our study was to evaluate emotional prosody recognition (EPR) in participants with amnestic mild cognitive impairment (aMCI) due to AD, AD dementia patients, and cognitively healthy controls and to measure volumes or thickness of the brain structures involved in this process. In addition, we correlated EPR score to cognitive impairment as measured by MMSE. The receiver operating characteristic (ROC) analysis was used to assess the ability of EPR tests to differentiate the control group from the aMCI and dementia groups. METHODS: Eighty-nine participants from the Czech Brain Aging Study: 43 aMCI due to AD, 36 AD dementia, and 23 controls, underwent Prosody Emotional Recognition Test. This experimental test included the playback of 25 sentences with neutral meaning each recorded with different emotional prosody (happiness, sadness, fear, disgust, anger). Volume of the amygdala and thickness of the TP, STS, and rostral and caudal parts of AC (RAC and CAC) were measured using FreeSurfer algorithm software. ANCOVA was used to evaluate EPR score differences. ROC analysis was used to assess the ability of EPR test to differentiate the control group from the aMCI and dementia groups. The Pearson's correlation coefficients were calculated to explore relationships between EPR scores, structural brain measures, and MMSE. RESULTS: EPR was lower in the dementia and aMCI groups compared with controls. EPR total score had high sensitivity in distinguishing between not only controls and patients, but also controls and aMCI, controls and dementia, and aMCI and dementia. EPR decreased with disease severity as it correlated with MMSE. There was a significant positive correlation of EPR and thickness of the right TP, STS, and bilateral RAC. CONCLUSIONS: EPR is impaired in AD dementia and aMCI due to AD. These data suggest that the broad range of AD symptoms may include specific deficits in the emotional sphere which further complicate the patient's quality of life.
INTRODUCTION: Path integration (PI) is an important component of spatial navigation that integrates self-motion cues to allow the subject to return to a starting point. PI depends on the structures affected early in the course of Alzheimer's disease (AD) such as the medial temporal lobe and the parietal cortex. OBJECTIVES: To assess whether PI is impaired in patients with mild AD and amnestic mild cognitive impairment (aMCI) and to investigate the role of the hippocampus, entorhinal and inferior parietal cortex in this association. METHODS: 27 patients with aMCI, 14 with mild AD and 18 controls completed eight trials of Arena Path Integration Task. The task required subjects with a mask covering their eyes to follow an enclosed triangle pathway through two previously seen places: start-place1-place2-start. Brains were scanned at 1.5T MRI and respective volumes and thicknesses were derived using FreeSurfer algorithm. RESULTS: Controlling for age, education, gender and Mini-Mental State Examination score the aMCI and AD subjects were impaired in PI accuracy on the pathway endpoint (p=0.042 and p=0.013) compared to controls. Hippocampal volume and thickness of entorhinal and parietal cortices explained separately 36-45% of the differences in PI accuracy between controls and aMCI and 28-31% of the differences between controls and AD subjects. CONCLUSIONS: PI is affected in aMCI and AD, possibly as a function of neurodegeneration in the medial temporal lobe structures and the parietal cortex. PI assessment (as a part of spatial navigation testing) may be useful for identification of patients with incipient AD.
- MeSH
- Alzheimerova nemoc komplikace diagnostické zobrazování MeSH
- kognitivní dysfunkce komplikace diagnostické zobrazování MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- mozek diagnostické zobrazování MeSH
- neuropsychologické testy MeSH
- percepční poruchy diagnostické zobrazování etiologie MeSH
- počítačové zpracování obrazu MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- studie případů a kontrol MeSH
- vnímání prostoru fyziologie MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
