- MeSH
- Academies and Institutes history organization & administration utilization MeSH
- Bayes Theorem MeSH
- Research Support as Topic MeSH
- Financing, Organized MeSH
- Risk Assessment methods utilization MeSH
- Humans MeSH
- Monte Carlo Method MeSH
- Probability MeSH
- Air Pollution, Radioactive analysis adverse effects MeSH
- Models, Statistical MeSH
- Environmental Pollution analysis adverse effects MeSH
- Check Tag
- Humans MeSH
When considering the probabilistic approach to neural networks in the framework of statistical pattern recognition we assume approximation of class-conditional probability distributions by finite mixtures of product components. The mixture components can be interpreted as probabilistic neurons in neurophysiological terms and, in this respect, the fixed probabilistic description contradicts the well known short-term dynamic properties of biological neurons. By introducing iterative schemes of recognition we show that some parameters of probabilistic neural networks can be "released" for the sake of dynamic processes without disturbing the statistically correct decision making. In particular, we can iteratively adapt the mixture component weights or modify the input pattern in order to facilitate correct recognition. Both procedures are shown to converge monotonically as a special case of the well known EM algorithm for estimating mixtures.
- MeSH
- Algorithms MeSH
- Humans MeSH
- Nerve Net MeSH
- Neural Networks, Computer MeSH
- Neurons physiology MeSH
- Recognition, Psychology MeSH
- Pattern Recognition, Automated MeSH
- Pattern Recognition, Visual physiology MeSH
- Models, Statistical MeSH
- Check Tag
- Humans MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
Je známo, že pro analýzu reliability testů, které se užívají pro měření v psychologické diagnostice, je k dispozici velice silná a podrobně rozpracovaná metodologie. V diagnostice se však vyskytují i rozličné klasifikační procedury, kdy observovaná proměnná má pouze nominální charakter. U takových klasifikací se informace o jejich reliabilitě vyskytuje velice vzácně. Jedním z důvodů je samozřejmě fakt, že pro nominální klasifikace není k dispozici tak vypracovaná metodologie, jako u testového měření. Analýza spolehlivosti je v těchto případech většinou založena na Cohen-Fleissově kappa koncepci, tedy analýze konkordance při dvou, nebo více replikacích klasifikace. Cílem této stati je prezentace nové, netradiční metody analýzy reliability klasifikačních procedur, jejímž základem je pravděpodobnostní model chyby v klasifikaci. Tento model je založen na analogickém principu jako „true-error“ model klasické teorie testů.
It is known that there is a very powerful and detailed methodology for a reliability analysis of tests that are used for the measurement in psychological diagnostics. However, there are also various diagnostic classification procedures in which observed variable is measured only on a nominal scale. For such classifications, the information about their reliability is available very rarely. Of course, one reason for this is the fact that there is no sufficiently developed methodology for the nominal classification, unlike for the test measurements. The analysis of reliability in these cases is usually based on the Cohen-Fleiss kappa conception, i.e. the concordance analysis of two or more replications of classification. The aim of this paper is to present new, innovative methods of the analysis of reliability of classification procedures, based on a probabilistic model of error in classification. This model is based on analogous principles as the „true-error“ model of classical test theory.
- MeSH
- Humans MeSH
- Mathematics MeSH
- Psychology * MeSH
- Statistics as Topic * MeSH
- Research * MeSH
- Check Tag
- Humans MeSH
The probabilistic two-stage model of cell killing by ionizing radiation enables to represent both damage induction by radiation and its repair by the cell. The model properties and applications as well as possible interpretation of the underlying damage classification are discussed. Analyses of published survival data for V79 hamster cells irradiated by protons and He, C, O, and Ne ions are reported, quantifying the variations in radiation quality with increasing charge and linear energy transfer of the ions.
- MeSH
- Cell Death radiation effects MeSH
- Cells radiation effects MeSH
- Financing, Organized MeSH
- Helium MeSH
- Radiation, Ionizing MeSH
- Ions MeSH
- Cricetinae MeSH
- Oxygen MeSH
- Neon MeSH
- Protons MeSH
- Models, Statistical MeSH
- Carbon MeSH
- Cell Survival radiation effects MeSH
- Animals MeSH
- Check Tag
- Cricetinae MeSH
- Animals MeSH
- MeSH
- Humans MeSH
- Probability MeSH
- Psychophysiology MeSH
- Visual Perception MeSH
- Check Tag
- Humans MeSH
BACKGROUND: Thalamic gliomas represent a great challenge for neurosurgeons because of the high surgical risk of damaging the surrounding anatomy. Preoperative planning may considerably help the surgeon find the most ideal operative trajectory, avoiding thalamic nuclei and important white matter pathways adjacent to the tumor tissue. Thalamic segmentation is a promising imaging tool based on diffusion tensor magnetic resonance imaging. It provides the possibility to predict the relationship of the tumor to thalamic nuclei. OBJECTIVE: To propose a new tool in thalamic glioma surgery that may help to differentiate between normal thalamus and tumor tissue, making preoperative planning possible and facilitating the choice of the optimal surgical approach and trajectory for neuronavigation-assisted surgery. METHODS: Four patients with thalamic gliomas preoperatively underwent conventional and diffusion-weighted magnetic resonance imaging conducted on 1.5 T. Subsequently, probabilistic tractography and thalamic segmentation were performed with the FSL Software as preoperative planning. We also present a case when thalamic segmentation was applied retrospectively using preoperative images. All patients went through neuronavigation-assisted surgery (1 partial, 4 subtotal resections). RESULTS: Surgery performed based on the output of thalamic segmentation caused no deterioration in the neurological symptoms of our patients. Indeed, we noticed improvement in the neurological condition in 3 cases; furthermore, in 2 patients, a concern-free state was achieved. CONCLUSION: We suggest that thalamic segmentation may be applied successfully and routinely in the surgical treatment of thalamic gliomas.
- MeSH
- Diffusion Magnetic Resonance Imaging MeSH
- Adult MeSH
- Glioma pathology surgery MeSH
- Humans MeSH
- Young Adult MeSH
- Brain Neoplasms pathology surgery MeSH
- Nerve Fibers pathology MeSH
- Neurosurgical Procedures methods MeSH
- Neuronavigation MeSH
- Image Processing, Computer-Assisted MeSH
- Aged MeSH
- Thalamus pathology MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Young Adult MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
