Smallest detectable change in volume differs between mass flow sensor and pneumotachograph

<p>Abstract</p> <p>Background</p> <p>To assess a pulmonary function change over time the mass flow sensor and the pneumotachograph are widely used in commercially available instruments. However, the smallest detectable change for both devices has never been compared. Therefore, the aim of this study is to determine the smallest detectable change in vital capacity (VC) and single-breath diffusion parameters measured by mass flow sensor and or pneumotachograph.</p> <p>Method</p> <p>In 28 healthy pulmonary function technicians VC, transfer factor for carbon monoxide (DLCO) and alveolar volume (VA) was repeatedly (10×) measured. The smallest detectable change was calculated by 1.96 x Standard Error of Measurement ×√2.</p> <p>Findings</p> <p>The mean (range) of the smallest detectable change measured by mass flow sensor and pneumotachograph respectively, were for VC (in Liter): 0.53 (0.46-0.65); 0.25 (0.17-0.36) (<it>p </it>= 0.04), DLCO (in mmol*kPa^-1*min^-1): 1.53 (1.26-1.7); 1.18 (0.84-1.39) (<it>p </it>= 0.07), VA (in Liter): 0.66. (0.53-0.82); 0.43 (0.34-0.53) (<it>p </it>= 0.04) and DLCO/VA (in mmol*kPa^-1*min^-1*L^-1): 0.22 (0.19-0.28); 0.19 (0.14-0.22) (<it>p </it>= 0.79).</p> <p>Conclusions</p> <p>Smallest detectable significant change in VC and VA as measured by pneumotachograph are smaller than by mass flow sensor. Therefore, the pneumotachograph is the preferred instrument to estimate lung volume change over time in individual patients.</p

A Mathematical Model for Interpretable Clinical Decision Support with Applications in Gynecology

Over time, methods for the development of clinical decision support (CDS) systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical models. In order to accomplish effective decision support, CDS systems should provide information on how the model arrives at a certain decision. To address the issue of incompatibility between performance, interpretability and applicability of CDS systems, this paper proposes an innovative model structure, automatically leading to interpretable and easily applicable models. The resulting models can be used to guide clinicians when deciding upon the appropriate treatment, estimating patient-specific risks and to improve communication with patients.We propose the interval coded scoring (ICS) system, which imposes that the effect of each variable on the estimated risk is constant within consecutive intervals. The number and position of the intervals are automatically obtained by solving an optimization problem, which additionally performs variable selection. The resulting model can be visualised by means of appealing scoring tables and color bars. ICS models can be used within software packages, in smartphone applications, or on paper, which is particularly useful for bedside medicine and home-monitoring. The ICS approach is illustrated on two gynecological problems: diagnosis of malignancy of ovarian tumors using a dataset containing 3,511 patients, and prediction of first trimester viability of pregnancies using a dataset of 1,435 women. Comparison of the performance of the ICS approach with a range of prediction models proposed in the literature illustrates the ability of ICS to combine optimal performance with the interpretability of simple scoring systems.The ICS approach can improve patient-clinician communication and will provide additional insights in the importance and influence of available variables. Future challenges include extensions of the proposed methodology towards automated detection of interaction effects, multi-class decision support systems, prognosis and high-dimensional data

Multiproject–multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy

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Correlations between Diffusion Tensor Imaging (DTI) and Magnetic Resonance Spectroscopy (1H MRS) in schizophrenic patients and normal controls

<p>Abstract</p> <p>Background</p> <p>Evidence suggests that white matter integrity may play an underlying pathophysiological role in schizophrenia. N-acetylaspartate (NAA), as measured by Magnetic Resonance Spectroscopy (MRS), is a neuronal marker and is decreased in white matter lesions and regions of axonal loss. It has also been found to be reduced in the prefrontal and temporal regions in patients with schizophrenia. Diffusion Tensor Imaging (DTI) allows one to measure the orientations of axonal tracts as well as the coherence of axonal bundles. DTI is thus sensitive to demyelination and other structural abnormalities. DTI has also shown abnormalities in these regions.</p> <p>Methods</p> <p>MRS and DTI were obtained on 42 healthy subjects and 40 subjects with schizophrenia. The data was analyzed using regions of interests in the Dorso-Lateral Prefrontal white matter, Medial Temporal white matter and Occipital white matter using both imaging modalities.</p> <p>Results</p> <p>NAA was significantly reduced in the patient population in the Medial Temporal regions. DTI anisotropy indices were also reduced in the same Medial Temporal regions. NAA and DTI-anisotropy indices were also correlated in the left medial temporal region.</p> <p>Conclusion</p> <p>Our results implicate defects in the medial temporal white matter in patients with schizophrenia. Moreover, MRS and DTI are complementary modalities for the study of white matter disruptions in patients with schizophrenia.</p

Modelling of a lead blast furnace

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Freeze lining formation of a synthetic lead slag

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Modelling of a submerged plasma process for Zn-containing residues treatment

A new high-temperature submerged plasma zinc fuming process has been developed for the treatment of zinc leach residues, EAF dusts and other zinc-containing waste materials. Continuous operation of this process requires high zinc fuming rates whilst retaining vessel integrity through the formation of a stable freeze lining. A zinc fuming process model using FactSage and ChemApp thermodynamic software has been developed, which simultaneously describes chemical, thermal and heat transfer outcomes of this process. The model has been used to systematically investigate the potential effects of operating parameters such as feed composition, fuel/oxygen ratio, electrical power and fluxing parameters on bath temperature, heat loss, Zn content in the slag.status: publishe