bluuebunny/crossref_metadata_2025_split huggingface dataset:
Herniation of the Bladder into the Rectum in a Dog
Authors: Lambrechts N. E. 
Published: March 2018

SummaryIn the dog, the pelvis is frequently injured following motor vehicle accidents (1). Injuries to the lower urinary and intestinal tracts may accompany pelvic fractures in man (2, 3, 4, 5) and the dog (1, 6, 7). This paper describes an unsual case of bladder retroflexion and herniation through a tear, into the rectum of a dog, following traumatic fracture of the pelvis. The successful management and repair is outlined and a biomechanical sequence leading to the abnormal bladder position is proposed.An unusual case of bladder retroflexion and herniation through a tear, into the rectum of a dog, following traumatic fracture of the pelvis is described. Repair was accomplished by manipulation of the bladder into its normal position through a coeliotomy incision and suturing of the rectal tear after prolapsing the rectum through the anus. The proposed biomechanical sequence leading to this injury is tearing by the inwardly rotated, fractured left hemipelvis as well as or alternatively, shearing forces along lines of excessive tension.
Averaging Signals with Random Time Shift and Time Scale Fluctuations
Authors: Meste O. , Muhammad W. , Rix H. 
Published: March 2018

Summary

Objectives:
Our main objective was to propose an alternative to the technique of signal averaging (SA) to avoid shape distortions due to jittering and scale fluctuations, leading to a mean shape signal rather than to an average one.

Methods:
In case of both time shift and time scale fluctuations of the individual signals, the first point was to show what model makes it possible to interpret their expected action as a linear shift invariant filter followed by a scale invariant one. So, even in the case of equal shape signals, the average is clearly not the same shape. The second point was to propose another averaging process, using the normalized integrals and called Shape Averaging (ShA) which provides, in this case, a mean signal preserving the common shape.

Results:
The performances of ShA were firstly shown by simulation. Shifted and scaled versions of a given signal, without and with additive noise, have been generated at random. The mean shape signal obtained by ShA was compared to the shifted and scaled signal using the exact average values of the shifts and scale factors. A very good reconstruction of the mean shape signal is obtained for SNR = 20 dB and quite good for 8 dB, especially compared to SA. The method was then applied to a series of M-waves coming from surface EMG signals. In this case, the comparison of ShA with SA makes it possible to appreciate the validity of equal shape signal hypothesis.
Automatic Decomposition of Wigner Distribution and its Application to Heart Rate Variability
Authors: Montano N. , Cerutti S. , Mainardi L. T. 
Published: March 2018

Summary

Objective:
We introduce an algorithm for the automatic decomposition of Wigner Distribution (WD) and we applied it for the quantitative extraction of Heart Rate Variability (HRV) spectral parameters during non-stationary events. Early response to tilt was investigated.

Methods:
Quantitative analysis of multi-components non-stationary signals is obtained through an automatic decomposition of WD based on least square (LS) fitting of the instantaneous autocorrelation function (ACF). Through this approach the different signal and interference terms which contributes to the ACF may be separated and their parameters (instantaneous frequency and amplitude) quantified. A beat-to-beat monitoring of HRV spectral components is obtained.

Results:
Analysis of simulated signals demonstrated the capability of the proposed approach to track and separate the signal components. Analysis of HRV data evidenced different dynamics in the early Autonomic Nervous System (ANS) response to tilt.

Conclusions:
The novel approach to the quantification of the beat-to-beat HRV spectral parameters obtained from decomposition of Wigner distribution was demonstrated to be effective in the analysis of HRV data. Relevant physiological information about the dynamics of the early sympathetic response to tilt were obtained. The method is a general approach which may be employed for a quantitative time-frequency analysis of non-stationary biological signals.
Estimating Respiratory Pattern Variability by Symbolic Dynamics
Authors: Mateu J. , Vallverdú M. , Giraldo B. , Benito S. , Voss A. , Caminal P. 
Published: March 2018

Summary

Objectives:
The traditional techniques of data analysis are often not sufficient to characterize the complex dynamics of respiration. In this study the respiratory pattern variability was analyzed using symbolic dynamics.

Methods:
A group of 20 patients on weaning trials from mechanical ventilation were studied at two different pressure support ventilation levels. Breath duration (TTOT) time series and the relation TI/TTOT, that contains the influence of inspiratory time (TI), were considered. Length-3 words and 3 different symbols were proposed. The incidence of the overlapping τ and the parameter α were analyzed.

Results:
From the breath duration time series, the distribution of words with probability of occurrence higher than 6% was concentrated on one word for low respiratory variability, whereas high variability was characterized by 4 words, presenting a statistically significant difference (p ≤ 0.0005). The probability occurrence of words “110” and “111” was also significantly different (p ≤ .0005) when comparing both variabilities.

Conclusion:
The analysis carried out obtained discriminant functions able to correctly classify all the testing set series. These results permit the consideration of symbolic dynamics as a promising methodology to study the respiratory pattern variability.
Assessment of Cardiovascular Autonomic Control by the Empirical Mode Decomposition
Authors: Neto E. P. , Custaud M. A. , Cejka J. C. , Abry P. , Frutoso J. , Gharib C. , Flandrin P. 
Published: March 2018

Summary

Objectives:
Heart-rate variability (HRV) is an interesting tool for assessing cardiac autonomic system control, but nonstationarities raise problematic issues. The objective of this paper is to show that adapted signal processing tools may cope with nonstationary situations and improve the analysis of HRV.

Methods:
We propose to use the recent method of Empirical Mode Decomposition (EMD), so as to analyze the cardiac sympatho-vagal balance on automatically extracted modes. The method, which is fully data-adaptive, consists in an iterative decomposition based on the idea that any signal can be locally represented as an oscillation superimposed to a more regular trend. When a signal is composed of distinct nonstationary components, EMD therefore achieves a time-varying filtering which effectively separates them.

Results:
The method has been applied to situations where postural changes occur, provoking instantaneous changes in heart rate as a result of autonomic modifications. In the considered application where the sympatho-vagal balance is quantified by comparing the low-frequency (LF) and high-frequency (HF) components of RR intervals, EMD automatically achieves a separation of these components upon which further processing can be carried. Visualizing the decomposition in the time-frequency plane, we can identify local events due to the postural changes, and we can assess a (time-varying) HF vs. LF discrimination without resorting to some fixed high-pass/low-pass filtering.

Conclusion:
Assessing cardiovascular autonomic control by resorting to LF/HF measurements may prove difficult in nonstationary situations where the use of a priori fixed filters can be questioned. Because it is both local and fully data-adaptive, EMD appears as an appealing and versatile pre-processing technique for overcoming some of the limitations that conventional spectral methods are faced with in nonstationary situations.
Prediction of Cardiovascular Risk in Hemodialysis Patients by Data Mining
Authors: Weller K. , Woetzel D. , Guthke R. , Schroeder K. , Stein G. , Pohlmeier R. , Vienken J. , Pfaff M. 
Published: March 2018

Summary

Objectives:
The objective of this work was to contribute to the development, validation and application of data mining methods for prediction in decision support systems in medicine. The particular focus was on the prediction of cardiovascular risk factors in hemodialysis patients, specifically the interventricular septum (IVS) thickness of the heart of individual patients as an important quantitative indicator to diagnose left ventricular hypertrophy. The work was based on data from 63 long-term hemodialysis patients of the KfH Dialysis Centre in Jena, Germany.

Methods:
The approach applied is based on data mining methods and involves four major steps: data based clustering, cluster based rule extraction, rulebase construction and cluster and rule based prediction. The methods employed include crisp and fuzzy algorithms. At each step, logical and medical validation of results was carried out. Different sets of randomly selected patient data were used to train, test and optimize the clusterbases and rulebases for prediction.

Results:
Using the best clusterbase/rulebase combination designed, the IVS thickness cluster (‘small’ or ‘large’) was predicted correctly for 30 of the 35 patients with known IVS values in the training data set; no patient was predicted incorrectly and 5 were parity predicted. For the test data set, 4 of the 6 patients with known IVS values were predicted correctly, no patient incorrectly and 2 parity. These results did not substantially differ from those obtained using the second best clusterbase/rulebase combination which was finally recommended for use based on further performance criteria. The prediction of the IVS thickness clusters of the 22 patients with unknown IVS values also yielded good results that were (and could only be) validated by a medical individual risk assessment of these patients.

Conclusions:
The approach applied proved successful for the cluster and rule based prediction of a quantitative variable, such as IVS thickness, for individual patients from other variables relevant to the problem. The results obtained demonstrate the high potential of the approach and the methods developed and validated to support decision-making in hemodialysis and other fields of medicine by individual risk prediction.
Objective Evaluation of Three-dimensional Image Registration Algorithms – Tools for Optimization and Evaluation
Authors: Morgenstern U. , Steinmeier R. , Uhlemann F. 
Published: March 2018

Summary

Objective:
The registration of medical volume data sets plays an important role when different images or modalities are used during computer-assisted surgical procedures. Nevertheless, it is often questionable how robust and accurate the underlying algorithms really are. Therefore, the goal is to foster the establishment of methods for an objective evaluation.

Method:
To reliably calculate the accuracy of registration algorithms, a reference transformation must be known. Due to the unknown perfect registration for real clinical data, the simulation of realistic data and successive affine transformations are employed. The simulation is based on models of the respective imaging modality where the dominant physical effects are taken into account. This gives the user full control over all simulation and transformation parameters. Finally, suitable quality measures are applied which allow a systematic evaluation of image registration accuracy by comparing the known theoretical result and the transformation calculated by the algorithm under investigation.

Results:
During the development of a new registration algorithm, the presented method proved to be a very valuable tool for optimization and evaluation of registration accuracy, since it allows objective numerical comparison of the calculated results.

Conclusions:
The presented method can be used during the development of algorithms for optimization and for quantitative comparison of different registration schemes. The respective software tool can automatically generate and transform simulated but realistic data. Employing suitable numerical quality measures, an objective evaluation of registration results can be easily obtained. Still, the validity of the relatively simple models has to be verified to draw reliable conclusions with respect to real data.
Multimodal Retinal Image Registration for Optic Disk Segmentation
Authors: Skokan M. , Kubečka L. , Wolf M. , Donath K. , Jan J. , Michelson G. , Niemann H. , Chrástek R. 
Published: March 2018

Summary

Objectives:
The analysis of the optic disk morphology with the means of the scanning laser tomography is an important step for glaucoma diagnosis. A method we developed for optic disk segmentation in images of the scanning laser tomograph is limited by noise, nonuniform illumination and presence of blood vessels. Inspired by recent medical research, we wanted to develop a tool for improving optic disk segmentation by registration of images of the scanning laser tomograph and color fundus photographs and by applying a method we developed for optic disk segmentation in color fundus photographs.

Methods:
The segmentation of the optic disk for glaucoma diagnosis in images of the scanning laser tomograph is based on morphological operations, detection of anatomical structures and active contours and has been described in a previous paper [1]. The segmentation of the optic disk in the fundus photographs is based on nonlinear filtering, Canny edge detector and a modified Hough transform. The registration is based on mutual information using simulated annealing for finding maxima.

Results:
The registration was successful 86.8% of the time when tested on 174 images. Results of the registration have shown a very low displacement error of a maximum of about 5 pixels. The correctness of the registration was manually evaluated by measuring distances between the real vessel borders and those from the registered image.

Conclusions:
We have developed a method for the registration of images of the scanning laser tomograph and fundus photographs. Our first experiments showed that the optic disk segmentation could be improved by fused information from both image modalities.
Registration of Biplane Angiography and Intravascular Ultrasound for 3D Vessel Reconstruction
Authors: Wawro M. , Müller H. , Wilke C. , Weichert F. 
Published: March 2018

Summary

Abstract:
If planned and applied correctly, intra-vascular brachytherapy (IVB) can significantly reduce the risk of restenosis after interventional treatment of stenotic arteries.

Objectives:
In order to facilitate computer-based IVB planning, a three-dimensional reconstruction of the stenotic artery based on intravascular ultrasound (IVUS) sequences is desirable.

Methods:
To attain a 3D reconstruction, the frames of the IVUS sequence are properly aligned in space and completed with additional intermediate frames generated by interpolation. The alignment procedure uses additional information that is obtained from biplane X-ray angiography performed simultaneously during the capturing of the IVUS sequence. After IVUS images and biplane angiography data are acquired from the patient, the vessel-wall borders and the IVUS catheter are detected by an active contour algorithm. Next, the twist between adjacent IVUS frames is determined by a sequential triangulation method combined with stochastic analysis.

Results:
The above procedure results in a 3D volume-model of the vessel, which also contains information from the IVUS modality. This data is sufficient for computer-based intravascular brachytherapy planning.

Conclusion:
The proposed methodology can be used to improve the current state-of-the-art IVB treatment planning by enabling computerized dosage computations on a highly accurate 3D model.
Electronic Patient Information – Pioneers and MuchMore
Authors: Giere W. 
Published: March 2018

Summary

Objectives:
This paper must fulfill three different tasks: First, to introduce the topic “Electronic Patient Information – Pioneers and MuchMore”, second, to introduce the invited authors of the symposium, and third, to serve as the author’s academic farewell lecture as professor emeritus.

Results:
The electronic patient record, with all its different kinds of patient information, can be structured in many ways. Here, an historical approach is presented with a primary focus on the development of an information system for in- and outpatients in Germany, especially in Frankfurt, but also in comparison with US systems. The “Stone Age” and “Bronze Age” of patient-related computer applications started with expensive and insufficient hardware, but some years later, the first systems for patient documentation, text generation, and data acquisition could be implemented. The “iron age” and “golden age” yielded until the mid-1970s, e.g. in Oakland, Boston, Salt Lake City, and Frankfurt, quite successful Hospital Information Systems with some special emphasis on natural language processing. The following dark years were filled primarily with administrative systems, but beginning in the early 1980s, an era of enlightenment started, e.g. with rather inexpensive and easy to use PC application, broadly distributed MUMPS systems, and improved thesaurus-based text analysis. Especially in modern times, the medical text processing and classifying has been extended and successfully applied.

Conclusions:
Somewhat in contrast to other approaches, in the future the use of medical linguistics for the development of a successful electronic patient record should be better supported. Electronic patient information should be available wherever and whenever needed. For this, intelligent and automated reporting and controlled data exchange is necessary. The computer should do all classification, coding, and administrative work, and the physician should get all relevant information necessary for decision making.
Research Opportunities and Challenges in 2005
Authors: Lindberg D. A. B. 
Published: March 2018

Summary

Objectives:
Biomedical informatics practice and research have become so broad that I will comment on only three areas. These are the electronic health record; prospective population studies; and interactive publications.

Methods:
Review of the literature, Internet resources and material and reports generated by internal and external research projects.

Results:
Development of an electronic health record continues to be problematic in the U.S. A number of large-scale prospective cohort studies of normal populations are now actively occurring or in planning stages in a number of countries; these present special research opportunities in biomedical informatics. Although there are engineering challenges to the implementation of interactive publications, they have the potential to enhance understanding, learning, and memory of scientific and health concepts.

Conclusions:
Three areas of bio-medical informatics challenge us and offer interesting and worthy research opportunities. These include the electronic health record, prospective cohort studies, and interactive publications.
Creative and Innovative Statistics in Clinical Research and Development
Authors: Maurer W. 
Published: March 2018

Summary

Objectives:
The aim of this paper is to show that even in a highly regulated area such as clinical research and development in pharmaceutical industry, there are needs and ample opportunities for statisticians and other medical informatics professionals to further creatively develop and implement methods in order to support the collection, analysis and interpretation of clinical data.

Methods:
The recently published “Critical Path” initiative of the US Food and Drug Administration discusses the decline in new drug submissions in the last decade and illustrates potential causes in the present clinical development process. Areas where statisticians can and have begun to look for new innovative ways to overcome these shortcomings are presented and examples of such novel approaches that have been developed by statistical methodologists in the pharmaceutical industry together with statisticians in academia are given.

Results:
In Early Development, i.e., in the first studies in man with a new compound, a combination of Bayesian methods and modeling approaches is particularly promising to increase the efficiency of decision making whereas in later phases (IIb and III) a marriage of modeling and classical frequentist approaches together with novel adaptive designs is expected to help to chose the right dose regimen and to perform the trials more efficiently in reduced time.

Conclusions:
The combination of known statistical methods and thinking and the development of new approaches are in line with the present paradigm of “learning and confirming” in regulated clinical development while increasing the efficiency of both.
Building Multivariable Regression Models with Continuous Covariates in Clinical Epidemiology
Authors: Sauerbrei W. , Royston P. 
Published: March 2018

Summary

Objectives:
In fitting regression models, data analysts must often choose a model based on several candidate predictor variables which may influence the outcome. Most analysts either assume a linear relationship for continuous predictors, or categorize them and postulate step functions. By contrast, we propose to model possible non-linearity in the relationship between the outcome and several continuous predictors by estimating smooth functions of the predictors. We aim to demonstrate that a structured approach based on fractional polynomials can give a broadly satisfactory practical solution to the problem of simultaneously identifying a subset of 'important' predictors and determining the functional relationship for continuous predictors.

Methods:
We discuss the background, and motivate and describe the multivariable fractional polynomial (MFP) approach to model selection from data which include continuous and categorical predictors. We compare our results with those from other approaches in examples. We present a small simulation study to compare the functional form of the relationship obtained by fitting fractional polynomials and splines to a single predictor variable.

Results:
We illustrate the advantages of the MFP approach over standard techniques of model construction in two real example datasets analyzed with logistic and Cox regression models, respectively. In the simulation study, fractional polynomial models had lower mean square error and more realistic behaviour than comparable spline models.

Conclusions:
In many practical situations, the MFP approach can satisfy the aim of finding models that fit the data well and also are simple, interpretable and potentially transportable to other settings.