- MeSH
- Child MeSH
- Attention Deficit Disorder with Hyperactivity physiopathology MeSH
- Cognition MeSH
- Humans MeSH
- Motor Skills MeSH
- Brain physiopathology MeSH
- Personality Tests MeSH
- Computers MeSH
- Reaction Time MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Male MeSH
- Publication type
- Comparative Study MeSH
- MeSH
- Electrocardiography, Ambulatory methods instrumentation utilization MeSH
- Electrocardiography classification methods trends MeSH
- Risk Assessment methods MeSH
- Myocardial Infarction diagnosis MeSH
- Humans MeSH
- Neural Networks, Computer MeSH
- Signal Processing, Computer-Assisted instrumentation MeSH
- Sensitivity and Specificity MeSH
- Statistics as Topic methods MeSH
- Check Tag
- Humans 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
- Algorithms * MeSH
- Biological Evolution * MeSH
- Genetic Fitness MeSH
- Humans MeSH
- Computer Simulation MeSH
- Image Processing, Computer-Assisted methods MeSH
- Signal-To-Noise Ratio MeSH
- Regression Analysis MeSH
- Software * MeSH
- Image Enhancement methods MeSH
- Computational Biology methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
The representation of carbohydrates in 3D space using symbols is a powerful visualization method, but such representations are lacking in currently available visualization software. The work presented here allows researchers to display carbohydrate 3D structures as 3D-SNFG symbols using LiteMol from a web browser (e.g., v.litemol.org/?loadFromCS=5T3X ). Any PDB ID can be substituted at the end of the URL. Alternatively, the user may enter a PDB ID or upload a structure. LiteMol is available at https://v.litemol.org and automatically depicts any carbohydrate residues as 3D-SNFG symbols. To embed LiteMol in a webpage, visit https://github.com/dsehnal/LiteMol .
Poruchy kognitivních funkcí u schizofrenie významně ovlivňují funkční výsledné stavy onemocnění. Kognitivní postižení se projevuje především v paměti, stavech pozornosti a ve vyšších exekutivních funkcích. Při pokusu o nápravu kognitivní dysfunkce se s částečným úspěchem využívá celá řada rehabilitačních programů, z nichž některé využívají i počítače. Dosavadní zkušenosti s počítačovou rehabilitací jsou nadějné, ukazuje se, že schizofrenní nemocní jsou schopni dokončit úlohy a jsou motivováni. Představujeme projekt počítačové rehabilitace kognitivního deficitu u schizofrenie, který využívá Bracyho program PSS CogReHab, a prezentujeme první zkušenosti s tímto rehabilitačním programem.
Impairment of cognitive functions in schizophrenia has a severe impact on the functional outcome of illness. Cognitive deficit can be detected in memory, attentional states, and executive functioning. Numerous rehabilitation programs are successfully used in remediation of cognitive dysfunction, some of them are computer-assisted. Experience with computer rehabilitation is encouraging, schizophrenic patients are able to complete tasks, they are motivated. We introduce a project of computer-assisted cognitive rehabilitation in schizophrenia using Bracy’s PSS CogReHab program, and present our first experience.
- MeSH
- Adult MeSH
- Cognition Disorders pathology rehabilitation MeSH
- Humans MeSH
- Neuropsychological Tests methods MeSH
- Therapy, Computer-Assisted methods MeSH
- Schizophrenia rehabilitation MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Female MeSH
- Publication type
- Case Reports MeSH
Kognice významně ovlivňuje průběh a funkční výsledné stavy schizofrenního onemocnění. Výsledný stav onemocnění je jen nepřímo ovlivnitelný farmakoterapií, která má limitovaný vliv na kognitivní funkce. V rehabilitaci kognitivního deficitu se často využívají také počítačové programy. V rámci CNS probíhá otevřená osmitýdenní studie sledující vliv počítačové rehabilitace pomocí Bracyho programu PSS CogReHab na výkon v neuropsychologických testech u schizofrenních nemocných. První výsledky u 12 nemocných (6 mužů a 6 žen) potvrdily zlepšení v některých kognitivních testech, v reprodukci Rey-Osterriethovy figury po 3 min (p = 0,024) a ve WCST: menší počet karet (p = 0,005), menší počet celkových chyb (p = 0,04), neperseveračních chyb (p = 0,02) a percentuální zlepšení konceptuální úrovně odpovědí (p = 0,04). Dalším pozitivním přínosem je zlepšení sociability pacientů a možnost okamžité zpětné vazby, kontroly vlastního výkonu. Předběžné výsledky ukazují potřebu soustředit pozornost na rehabilitaci pracovní a dlouhodobé paměti a verbálních parametrů.
Cognition has a significant impact on the course and functional outcome of schizophrenia. Disorder outcome can be affected by drug treatment only indirectly; drugs have a limited effect on cognitive functions. Computer programs are frequently used in rehabilitation of cognitive deficit. There is an open, eight-week study conducted in the CNS, investigating effects of computer-assisted rehabilitation with Bracy’s PSS CogReHab program on cognition in schizophrenia. First results in 12 subjects (6 males and 6 females) indicate improvement in some neuropsychological tests, reproduction of Rey-Osterrieth Figure after 3 min (p = 0.024) and in the WCST: decreased number of administered cards (p = 0.005), lower number of total errors (p = 0.04), non-perseverative errors (p = 0.02) and improvement in the percentage of conceptual response level (p = 0.04). Other positive findings include improvement of patients social life and immediate feedback, own control of action. Preliminary results suggest that more attention should be focused on rehabilitation of working and long-term memory and verbal parameters.
- MeSH
- Adult MeSH
- Research Support as Topic MeSH
- Cognition Disorders etiology rehabilitation MeSH
- Humans MeSH
- Neuropsychological Tests MeSH
- Computers MeSH
- Rehabilitation methods instrumentation MeSH
- Schizophrenia diagnosis rehabilitation MeSH
- Software MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Review MeSH
- Comparative Study MeSH
... Computer-based patient records. ... ... Patient perspectives on computer-based medical records. ... ... A computer system for skeletal growth measurement. ... ... Multichannel EEG-based brain-computer communication. ... ... Methods and Programs in Medicine Computers in Biology and Medicine Computers and Biomedical Research ...
viii, 650 stran : ilustrace, tabulky ; 28 cm
- MeSH
- Medical Records Systems, Computerized MeSH
- Knowledge Management MeSH
- Decision Support Techniques MeSH
- Image Processing, Computer-Assisted MeSH
- Signal Processing, Computer-Assisted MeSH
- Health Services Administration MeSH
- Education, Medical MeSH
- Health Information Systems MeSH
- Publication type
- Collected Work MeSH
- Conspectus
- Lékařské vědy. Lékařství
- NML Fields
- lékařská informatika
- NML Publication type
- ročenky
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.
Cíl: Účelem této studie bylo zhodnotit neuropsychologickou rehabilitaci pomocí 12týdenního počítačového programu, aby se zjistilo, zda to mělo vliv na zlepšení kognitivních funkcí; také k identifikaci metod, které lze použít k měření tohoto účinku. Cílem této studie je demonstrovat účinek zvoleného vzdělávacího plánu a výsledný stav kognitivních funkcí. Metodika: Pacienti s diagnózou RS (43) byli randomizováni do dvou skupin - experimentální skupiny (26) a kontrolní skupiny (17). Všichni pacienti měli kognitivní defekt, který byl vyhodnocen na začátku studie. Po účasti na vzdělávacím programu byly výsledky monitorovány pomocí neuropsychologických testů. Účastníkům experimentální skupiny byla poskytnuta rehabilitace kognitivních funkcí pomocí počítačového tréninkového programu, který absolvovali doma. Proběhlo 32 školení, která se konala ve stanovených dnech s konkrétním podrobným plánem školení. Výsledky: Neuropsychologické testy použité na začátku a na konci studie prokázaly pozitivní účinek vzdělávacího programu. K největšímu zlepšení došlo v oblastech krátkodobé paměti a pozornosti. Závěr: Výsledky ukázaly, že u těch pacientů s RS, kteří se řídili plánem počítačového výcviku, došlo k pozitivním účinkům neuropsychologické rehabilitace.
Aim: The purpose of this study was to evaluate neuropsychological rehabilitation using a 12-week computer program to assess if it had an effect on improving cognitive functions and to identify methods that can be used to measure this effect. The aim of this study is to demonstrate the effect of the chosen educational plan and the resulting state of cognitive functions. Methods: Patients diagnosed with MS (43) were randomized into two groups - the experimental group (26) and the control group (17). All patients had a cognitive defect that was assessed at the beginning of the study. After participating in the training program, the results were monitored using neuropsychological tests. Participants in the experimental group were given their rehabilitation of cognitive functions using a computer training program which they undertook at home. There were 32 training sessions which took place on predetermined days with a specific detailed training plan. Results: The neuropsychological tests used at the beginning and the end of the study showed the positive effect of the training program. The greatest improvement was seen in the areas of immediate memory and attention. Conclusion: The results showed that in MS patients who followed the computer training plan, there were positive effects of the neuropsychological rehabilitation.
- Keywords
- počítačový trénink kognitivních funkcí,
- MeSH
- Cognitive Dysfunction rehabilitation MeSH
- Cognitive Remediation * methods MeSH
- Humans MeSH
- Neuropsychological Tests MeSH
- Neurological Rehabilitation methods MeSH
- Memory MeSH
- Therapy, Computer-Assisted methods MeSH
- Attention MeSH
- Randomized Controlled Trials as Topic MeSH
- Multiple Sclerosis * rehabilitation MeSH
- Check Tag
- Humans MeSH
- Male MeSH
- Female MeSH