•Bayesian model averaging for predicting survival probabilities of injured patients.•Reliable estimation of uncertainty in trauma injury severity scoring.•A web application available for trauma care ...practitioners.
Health care practitioners analyse possible risks of misleading decisions and need to estimate and quantify uncertainty in predictions. We have examined the “gold” standard of screening a patient's conditions for predicting survival probability, based on logistic regression modelling, which is used in trauma care for clinical purposes and quality audit. This methodology is based on theoretical assumptions about data and uncertainties. Models induced within such an approach have exposed a number of problems, providing unexplained fluctuation of predicted survival and low accuracy of estimating uncertainty intervals within which predictions are made. Bayesian method, which in theory is capable of providing accurate predictions and uncertainty estimates, has been adopted in our study using Decision Tree models. Our approach has been tested on a large set of patients registered in the US National Trauma Data Bank and has outperformed the standard method in terms of prediction accuracy, thereby providing practitioners with accurate estimates of the predictive posterior densities of interest that are required for making risk-aware decisions.
•Reliable estimation of uncertainty in trauma injury severity scoring and survival prediction.•Bayesian model averaging improves the prediction accuracy, precision and sensitivity.•A web application ...available for trauma care practitioners.
For making reliable decisions, practitioners need to estimate uncertainties that exist in data and decision models. In this paper we analyse uncertainties of predicting survival probability for patients in trauma care. The existing prediction methodology employs logistic regression modelling of Trauma and Injury Severity Score (TRISS), which is based on theoretical assumptions. These assumptions limit the capability of TRISS methodology to provide accurate and reliable predictions.
We adopt the methodology of Bayesian model averaging and show how this methodology can be applied to decision trees in order to provide practitioners with new insights into the uncertainty. The proposed method has been validated on a large set of 447,176 cases registered in the US National Trauma Data Bank in terms of discrimination ability evaluated with receiver operating characteristic (ROC) and precision–recall (PRC) curves.
Areas under curves were improved for ROC from 0.951 to 0.956 (p = 3.89 × 10−18) and for PRC from 0.564 to 0.605 (p = 3.89 × 10−18). The new model has significantly better calibration in terms of the Hosmer–Lemeshow Hˆ statistic, showing an improvement from 223.14 (the standard method) to 11.59 (p = 2.31 × 10−18).
The proposed Bayesian method is capable of improving the accuracy and reliability of survival prediction. The new method has been made available for evaluation purposes as a web application.
► We analysed the age-related patterns in newborn EEG. ► The use of posterior information about EEG features has improved the assessment. ► The accuracy of the proposed Bayesian assessments slightly ...outperformed the expert assessments.
EEG experts can assess a newborn’s brain maturity by visual analysis of age-related patterns in sleep EEG. It is highly desirable to make the results of assessment most accurate and reliable. However, the expert analysis is limited in capability to provide the estimate of uncertainty in assessments. Bayesian inference has been shown providing the most accurate estimates of uncertainty by using Markov Chain Monte Carlo (MCMC) integration over the posterior distribution. The use of MCMC enables to approximate the desired distribution by sampling the areas of interests in which the density of distribution is high. In practice, the posterior distribution can be multimodal, and so that the existing MCMC techniques cannot provide the proportional sampling from the areas of interest. The lack of prior information makes MCMC integration more difficult when a model parameter space is large and cannot be explored in detail within a reasonable time. In particular, the lack of information about EEG feature importance can affect the results of Bayesian assessment of EEG maturity. In this paper we explore how the posterior information about EEG feature importance can be used to reduce a negative influence of disproportional sampling on the results of Bayesian assessment. We found that the MCMC integration tends to oversample the areas in which a model parameter space includes one or more features, the importance of which counted in terms of their posterior use is low. Using this finding, we proposed to cure the results of MCMC integration and then described the results of testing the proposed method on a set of sleep EEG recordings.
The H7 system was populated in the H2(He8,He3)H7 reaction with a 26 AMeV He8 beam. The H7 missing mass energy spectrum, the H3 energy and angular distributions in the H7 decay frame were ...reconstructed. The H7 missing mass spectrum shows a peak, which can be interpreted either as unresolved 5/2+ and 3/2+ doublet or one of these states at 6.5(5) MeV. The data also provide indications of the 1/2+ ground state of H7 located at 1.8(5) MeV with quite a low population cross section of ∼25 μb/sr within angular range θc.m.≃(17°-27°).
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This work is devoted to studying the effects of non-magnetic shell coating on nanoparticles in a low frequency alternating magnetic field (LF AMF) on tumor cells in vitro. Two types ...of iron oxide nanoparticles with the same magnetic core with and without silica shells were synthesized. Nanoparticles with silica shells significantly decreased the viability of PC3 cancer cells in a low frequency alternating magnetic field according to the cytotoxicity test, unlike uncoated nanoparticles. We showed that cell death results from the intracellular membrane integrity failure, and the calcium ions concentration increase with the subsequent necrosis. Transmission electron microscopy images showed that the uncoated silica nanoparticles are primarily found in an aggregated form in cells. We believe that uncoated nanoparticles lose their colloidal stability in an acidic endosomal environment after internalization into the cell due to surface etching and the formation of aggregates. As a result, they encounter high endosomal macromolecular viscosity and become unable to rotate efficiently. We assume that effective rotation of nanoparticles causes cell death. In turn, silica shell coating increases nanoparticles stability, preventing aggregation in endosomes. Thus, we propose that the colloidal stability of magnetic nanoparticles inside cells is one of the key factors for effective magneto-mechanical actuation.
NeuRad detector prototype pulse shape study Muzalevsky, I.; Chudoba, V.; Belogurov, S. ...
EPJ Web of Conferences,
01/2018, Volume:
177
Journal Article, Conference Proceeding
Peer reviewed
Open access
The EXPERT setup located at the Super-FRS facility, the part of the FAIR complex in Darmstadt, Germany, is intended for investigation of properties of light exotic nuclei. One of its modules, the ...high granularity neutron detector NeuRad assembled from a large number of the scintillating fiber is intended for registration of neutrons emitted by investigated nuclei in low-energy decays. Feasibility of the detector strongly depends on its timing properties defined by the spatial distribution of ionization, light propagation inside the fibers, light emission kinetics and transition time jitter in the multi-anode photomultiplier tube. The first attempt of understanding the pulse formation in the prototype of the NeuRad detector by comparing experimental results and Monte Carlo (MC) simulations is reported in this paper.
A neutron spectrometer based on stilbene crystals has been developed by the Flerov Laboratory of Nuclear Reactions at the Joint Institute for Nuclear Research (Dubna, Russia). The timing resolution ...is determined as a function of the signal amplitude (σ
T
= 0.18 ns at an amplitude of 1 MeV in the electron equivalent). The measured energy resolution of the detecting modules for γ rays is σ
E
/
E
= 4.5% at
E
= 1 MeV. The quality of the
n
–γ discrimination is investigated. It is shown that reliable discrimination is possible, beginning with a deposited energy of 100 keV in the electron equivalent, which corresponds to the kinetic energy of recoil protons of ∼700 keV. The neutron spectrometer helps to significantly expand the experimental capabilities and to carry out correlation experiments with radioactive beams on the ACCULINNA-2 fragment separator at a new level of quality.
We describe a new technique developed for an automated recognition of solar filaments visible in Ha hydrogen line full-disk spectroheliograms. These filaments are difficult to recognize because of ...variability in the background caused by atmospheric conditions. The presented technique is based on an artificial neural network (ANN) consisting of two hidden neurons and one output neuron which learn to exclude the contribution of a changeable background to a filament. The ANN is trained on a single image fragment labeled manually to recognize the filament elements depicted on a local background. The background contribution is approximated with linear and parabolic functions. This technique applied to the filament recognition in 54 cropped images reveals better detection results for a parabolic approximation than for a linear one approaching an accuracy of about 82% of the total filament pixels.
Due to conceptual difference between geometry descriptions in Computer-Aided Design (CAD) systems and particle transport Monte Carlo (MC) codes direct conversion of detector geometry in either ...direction is not feasible. The paper presents an update on functionality and application practice of the CATIA-GDML geometry builder first introduced at CHEP2010. This set of CATIAv5 tools has been developed for building a MC optimized GEANT4/ROOT compatible geometry based on the existing CAD model. The model can be exported via Geometry Description Markup Language (GDML). The builder allows also import and visualization of GEANT4/ROOT geometries in CATIA. The structure of a GDML file, including replicated volumes, volume assemblies and variables, is mapped into a part specification tree. A dedicated file template, a wide range of primitives, tools for measurement and implicit calculation of parameters, different types of multiple volume instantiation, mirroring, positioning and quality check have been implemented. Several use cases are discussed.
Investigation of the
7
H-system in the experiment conducted at the fragment separator ACCULINNA-2 in the
8
He(
2
H,
3
He)
7
H reaction requires to detect the recoil
3
He ions with energy down to 6 ...MeV. For this purpose two
particle telescopes are used, with each telescope having in front a thin (20-μm) Si strip detector (
). The maps of thickness heterogeneity of the thin detectors were determined by measuring the energy losses of the
226
Ra α-particles. The adopted thickness normalization method provides a good identification of the
3
He nuclei being recorded in the presence of a high
4
He background. Two approaches were used for calculating the energy losses of the identified
3
He and
4
He reaction ejectiles and reconstructing their energy values available at the exit from the deuterium target. The developed techniques were applied for the
7
H missing-mass reconstruction.
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