bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hardware, Software, Peopleware, Subjectivity
Authors: Grémy François 
Published: March 2018

Summary

Objective:
This paper develops the closing address the author was asked to deliver at the MEDINFO 2004 Congress in San Francisco.

Method:
Starting from three working conferences, dealing with evaluation of health information systems, where he was involved, the author describes the evolution of his personal ideas.

Results and Conclusions:
First he proposes the main distinction between systems where the user(s) remain(s) external from the running program, from the ones where the user(s) interacting with the program become(s) the main component of the system.In the first case, the methods of evaluation are the conventional methods used in Medical Technology Assessment. In the second case, the whole knowledge in anthropology (considered in its broadest meaning), may contribute strongly to evaluation.It becomes clear that the subjectivity of the user(s), how he (or they) react(s) with the computing machinery, is a main key to the success or failure of the whole system.As the eradication of subjectivity is often considered, since the beginning of “modern times”, as a condition for progress, the author claims that such a temptation is deleterious for our civilization threatened by a comeback of barbarity, and is scientifically wrong.For that demonstration, he calls on both philosophical concepts (from Aristotle to E. Husserl, M. Henry and J. Searle), and the most recent advances of neurosciences.
Normalization for Two-channel Microarray Data
Authors: Ittrich C. 
Published: March 2018

Summary

Objectives:
In two-channel microarray experiments the measured gene expression levels are affected by many sources of systematic variation. Normalization refers to the process of removing such systematic sources of variation, to make measured intensities within and between slides comparable. Some commonly used normalization methods removing intensity-dependent dye bias and adjusting differences in variability between slides will be reviewed with the main focus on intensity-dependent normalization methods.

Methods:
This article describes different intensity-dependent within-slide normalization methods for the log ratios of red and green channel intensities but also refers to single channel normalization methods incorporating all single channels of the slides at once.

Results:
The described procedures provide a useful approach to remove systematic sources of variation like intensity-dependent dye bias and variability between slides in cDNA microarray experiments. This is illustrated by an experimental data set.

Conclusions:
Several reasonable normalization procedures for two-channel microarray data have recently been proposed. Deciding on which method would perform well for a concrete experiment is difficult. Designed spike-in experiments or dilution series with known differences for some selected genes would be helpful to assess the different methods, but may be impractical for most laboratories due to the high costs.
Multiplicity Issues in Microarray Experiments
Authors: Landgrebe J. , Brunner E. , Bretz F. 
Published: March 2018

Summary

Objectives:
Discussion of different error concepts relevant to microarray experiments. Review of some commonly used multiple testing procedures. Comparison of different approaches as applied to gene expression data.

Methods:
This article focuses on familywise error rate (FWER) and false discovery rate (FDR) controlling procedures. Methods under investigation include: Bonferroni-type methods and their improvements (including resampling approaches), modified Bonferroni methods, data-driven approaches, as well as the linear step-up method and its modifications. Particular emphasis lies on the description of the assumptions, advantages and limitations for the investigated methods.

Results: FWER controlling procedures are often too conservative in high dimensional screening studies. A better balance between the raw P-values and the stringent FWER-adjusted P-values may be required in many situations, as provided by FDR controlling and related procedures.

Conclusions:
The questions remain open, which error concept to apply and which multiple testing procedure to use. Although we believe that the FDR or one of its variants will be applied more often in the future, longterm experience with microarray technology is missing and thus the validity of appropriate multiple test procedures cannot yet be assessed for microarray data analysis.
Molecular Diagnosis
Authors: Spang R. , Markowetz F. 
Published: March 2018

Summary

Objectives:
We discuss supervised classification techniques applied to medical diagnosis based on gene expression profiles. Our focus lies on strategies of adaptive model selection to avoid overfitting in high-dimensional spaces.

Methods:
We introduce likelihood-based methods, classification trees, support vector machines and regularized binary regression. For regularization by dimension reduction, we describe feature selection methods: feature filtering, feature shrinkage and wrapper approaches. In small sample-size situations efficient methods of data re-use are needed to assess the predictive power of a model. We discuss two issues in using cross-validation: the difference between in-loop and out-of-loop feature selection, and estimating model parameters in nested-loop cross-validation.

Results:
Gene selection does not reduce the dimensionality of the model. Tuning parameters enable adaptive model selection. The feature selection bias is a common pitfall in performance evaluation. Model selection and performance evaluation can be combined by nested-loop cross-validation.

Conclusions:
Classification of microarrays is prone to overfitting. A rigorous and unbiased assessment of the predictive power of the model is a must.
Clustering Algorithms and Other Exploratory Methods for Microarray Data Analysis
Authors: Rahnenführer J. 
Published: March 2018

Summary

Objectives:
We introduce methods for the exploratory analysis of microarray data, especially focusing on cluster algorithms. Benefits and problems are discussed.

Methods:
We describe application and suitability of unsupervised learning methods for the classification of gene expression data. Cluster algorithms are treated in more detail, including assessment of cluster quality.

Results:
When dealing with microarray data, most cluster algorithms must be applied with caution. As long as the structure of the true generating models of such data is not fully understood, the use of simple algorithms seems to be more appropriate than the application of complex black-box algorithms. New methods explicitly targeted to the analysis of micro-array data are increasingly being developed in order to increase the amount of useful information extracted from the experiments.

Conclusions:
Unsupervised methods can be a helpful tool for the analysis of microarray data, but a critical choice of the algorithm and a careful interpretation of the results are required in order to avoid false conclusions.
Testing Differential Gene Expression in Functional Groups
Authors: Meister R. , Mansmann U. 
Published: March 2018

Summary

Objectives:
Single genes are not, in general, the primary focus of gene expression experiments. The researcher might be more interested in relevant pathways, functional sets, or genomic regions consisting of several genes. Efficient statistical tools to handle this task are of interest to research of biology and medicine.

Methods:
A simultaneous test on phenotype main effect and gene-phenotype interaction in a two-way layout linear model is introduced as a global test on differential expression for gene groups. Its statistical properties are compared with those of the global test for groups of genes by Goeman et al. [5] in a preliminary simulation study. The procedure presented also allows adjusting for covariates.

Results:
The proposed ANCOVA global test is equivalent to Goeman’s global test in a setting of independent genes. In our simulation setting for correlated genes, both tests lose power, however with a stronger loss for Goeman’s test. Especially in cases where the asymptotic distribution cannot be used, the stratified use of the ANCOVA global test shows a better performance than Goeman’s test.

Conclusions:
Our ANCOVA-based approach is a competitive alternative to Goeman’s global test in assessing differential gene expression between groups. It can be extended and generalized in several ways by a modification of the projection matrix.
Microarray Annotation and Biological Information on Function
Authors: Brors B. 
Published: March 2018

Summary

Objectives:
Many methods for statistical analysis of gene expression studies by DNA microarrays produce lists of genes as output. To understand gene lists in terms of traditional biology, e.g. which pathways may be affected, it is necessary to get appropriate annotations for the probes on an array.

Methods:
Problems arise with the different sources that have been used by manufacturers to design microarray probes, and their association to biological entities like genes, transcripts and proteins. Function annotation is of crucial importance, and systems like Gene Ontology can be used for this purpose. It arranges annotation terms in a hierarchical manner and thus makes annotations in a gene list amenable to automated analysis.

Results:
Several methods for analyses of gene function are described. The hierarchical nature of systems like Gene Ontology particularly suggests using methods from graph theory.

Conclusions:
The main problem in annotating micro-array probes and inferring affected functional modules is the incompleteness and degree of error in current biological databases. Initial approaches to make use of functional annotation exist, but have to be extended, in particular with respect to estimating the statistical significance of results.
A Computer Program to Estimate Power and Relative Efficiency of Flexibly Matched Case-control Studies
Authors: Gefeller O. , Brenner H. , Stürmer T. 
Published: March 2018

Summary

Objectives:
We recently introduced the concept of flexible matching strategies with varying proportions of a dichotomous matching factor among controls to increase power and efficiency of case-control studies. We now present a method and a computer program to calculate power and relative efficiency compared to an unmatched design varying the proportion of the matching factor in controls over all possible values from 0 to 100 percent.

Methods:
For all these values, the program calculates the expected variance of the combined Mantel-Haenszel odds ratio and determines the power using the standard error of the expected combined Mantel-Haenszel odds ratio under the null hypothesis as derived from the Mantel-Haenszel test statistic without continuity correction.

Results:
Thereby, the program allows estimating the optimal prevalence of the matching factor in selected controls for a given scenario which often differs from the prevalence in cases. It furthermore allows to estimate loss in power and efficiency compared to optimal matching by suboptimal matching.

Conclusions:
Estimations like these are helpful with respect to the decision when to stop efforts to optimize the degree of matching during the recruitment of controls. Our program will strongly facilitate assessing the benefits of flexible matching strategies.
Migration of Legacy Mumps Applications to Relational Database Servers
Authors: O’Kane K. C. 
Published: March 2018

Abstract:An extended implementation of the Mumps language is described that facilitates vendor neutral migration of legacy Mumps applications to SQL-based relational database servers. Implemented as a compiler, this system translates Mumps programs to operating system independent, standard C code for subsequent compilation to fully stand-alone, binary executables. Added built-in functions and support modules extend the native hierarchical Mumps database with access to industry standard, networked, relational database management servers (RDBMS) thus freeing Mumps applications from dependence upon vendor specific, proprietary, unstandardized database models. Unlike Mumps systems that have added captive, proprietary RDMBS access, the programs generated by this development environment can be used with any RDBMS system that supports common network access protocols. Additional features include a built-in web server interface and the ability to interoperate directly with programs and functions written in other languages.
Nonparametric Frontier Model as a Tool for Exploratory Analysis of Hospital Stays
Authors: Beguin C. 
Published: March 2018

Abstract:Diagnosis-related groups (DRG) were introduced in 1995 to the Belgian hospital financing system. Trimming rules are generally used when mean length of stay (LOS) is estimated by DRG. This paper proposes the use of frontier models instead of trimming rules. These models allow to take into account the characteristics of the patients, to rank hospital stays, and to indicate stays presenting discrepancy between the patient’s characteristics and the resources consumed. The analysis is done with the nonparametric Free Disposal Hull (FDH) model and the method developed by Wilson to detect extreme observations, when defining the frontier is adapted to analyze large databases.
A Measurement Model of Disease Severity in Absence of a Gold Standard
Authors: Martus P. 
Published: March 2018

Abstract:In the absence of a gold standard, we propose the use of confirmatory factor analysis for the quantification of agreement between diagnostic measurements and the true disease severity. The essential assumption is conditional independence of diagnostic measurements adjusted for the severity of the disease. However, depending on the number of measurements available, the method works even if some of them are conditionally dependent. We illustrate the method using an example related to glaucoma eye disease.
Influence of the Method of Data Collection on the Documentation of Blood-pressure Readings with an Anesthesia Information Management System (AIMS)
Authors: Junger A. , Quinzio L. , Fuchs C. , Michel A. , Sciuk G. , Marquardt K. , Dudeck J. , Hempelmann G. , Benson M. 
Published: March 2018

Abstract:The influence of methods for record keeping on the documentation of vital signs was assessed for the Anesthesia Information Management System (AIMS) NarkoData. We compared manually entered blood-pressure readings with automatically collected data. These data were stored in a database and subsequently evaluated and analyzed. The data sets were split into two groups, ”manual“ and ”automatic“. We evaluated the effect of automatic data collection on the incidence of corrected data, data validity and data variation. Blood-pressure readings of 37,726 data sets were analyzed. We could assess that the method of documentation did influence the data quality. It could not be assessed whether the incorrectness of data during automatic data gathering was caused by artefacts or by the anesthesiologist.
Adaptable Preprocessing Units and Neural Classification for the Segmentation of EEG Signals
Authors: Jäger H. , Witte H. , Galicki M. , Schelenz C. , Specht M. , Reinhart K. , Eiselt M. , Doering A. 
Published: March 2018

AbstractIn this contribution, a methodology for the simultaneous adaptation of preprocessing units (PPUs) for feature extraction and of neural classifiers that can be used for time series classification is presented. The approach is based upon an extension of the backpropagation algorithm for the correction of the preprocessing parameters. In comparison with purely neural systems, the reduced input dimensionality improves the generalization capability and reduces the numerical effort. In comparison with PPUs with fixed parameters, the success of the adaptation is less sensitive to the choice of the parameters. The efficiency of the developed method is demonstrated via the use of quadratic filters with adaptable transmission bands as preprocessing units for the segmentation of two different types of discontinuous EEG: discontinuous neonatal EEG (burst-interburst segmentation) and EEG in deep stages of sedation (burst-suppression segmentation).
Quantifying Stenosis in Renal Arteriograms: A Fuzzy Syntactic Analysis
Authors: Lalande A. , Cherrak I. , Brunotte F. , Degoulet P. , Jaulent M.C. 
Published: March 2018

AbstractThe introduction of fuzzy logic improves a system for the automatic quantification of renal artery lesions seen in digital subtraction angiograms. A two-step approach has been followed. An earlier system based on non-fuzzy syntactic analysis provided a clear symbolic description of the stenotic lesions. Although this system worked correctly, it did not take into account the variability and uncertainty inherent to image processing and to knowledge on the reference diameter. This system has been improved by the introduction of fuzzy logic in the representation of the reference diameter. It provides a description of the stenosis in terms of fuzzy quantities. To illustrate the benefits of the fuzzy approach, the results of the two systems have been compared by plotting the differences of an index of variability. It appears that the differences are statistically different when using a two-tailed paired t-test (t = 2.37; p = 0.025). The result shows that the fuzzy approach is better than a non-fuzzy approach in the sense that the index of variability is reduced significantly.
Design and Introduction of an Electronic Patient Record: How to Involve Users?
Authors: Faber M. G. 
Published: March 2018

Summary
Objectives: Two forms of participatory design (PD) – management-dominated and end-users focused – are described in the design and introduction of an electronic patient record (EPR) for a mental health care centre.
Methods: Qualitative research methods were used to achieve a ‘fine-grained’ insight into the EPR development process and its impacts. These methods included interviews, document study and observation of project group meetings.
Results: Management-dominated PD is highly structured, led by managers and centred around rationalisation of work. End-user focused PD is more bottom-up oriented. Central in this approach are users’ working patterns and user needs. In the case described, both forms actually lead to a poorly functioning EPR. It is explained why these results could be expected.
Conclusion: Our findings suggest not to reject PD, but to find a more appropriate balance between the two forms of PD.
Order Creation and Communication in Healthcare
Authors: Lavelle M. B. , Ash J. S. , Gorman P. N. 
Published: March 2018

Summary
Objectives: The aim of this paper is to examine the adequacy of the concept of Physician Order Entry (POE) as a model for clinical systems, and to suggest an alternative understanding of the order creation and communication process.
Methods: The study is based on an interpretative analysis of POE as a model for clinical systems and the results of our recent fieldwork.
Results: Observations from our recent fieldwork suggest that orders, like patient care in general, emerge from interactions among patients, physicians, nurses, family members, and others, employing a variety of technologies and information resources in the process. Orders as we have observed them originate, are negotiated, and are carried out in a dynamically evolving group with fluctuating membership and shifting role responsibilities. Furthermore, orders by themselves represent only a partial picture of what is done for the patient.
Conclusion: We argue that information systems are more likely to be helpful if they accommodate and facilitate POE as a multidisciplinary collaboration effort and fit better into the larger system of patient care.
Utility of the Charlson Comorbidity Index Computed from Routinely Collected Hospital Discharge Diagnosis Codes
Authors: Lim L. L.-Y. , O’Connell R. L. 
Published: March 2018

Abstract:This study aims to determine whether the Charlson comorbidity index computed from ICD-9-CM discharge diagnosis codes adds additional information to a model containing adjustment for more informed patient details (e.g., disease severity and history), besides solely age and sex, when predicting long-term survival. We conducted a retrospective cohort study of patients admitted to hospital for suspected acute myocardial infarction. Index scores were calculated by applying the D’Hoore et al. algorithm (1993). The index significantly improved the model fit (likelihood ratio test: p <0.001). The D’Hoore-adapted Charlson index is a useful comorbidity risk adjustment tool when applied to AMI and angina patients.
Statistical Support for Uncertainty in Radiological Diagnosis
Authors: Teather B. A. , Jeffery N. P. , du Boulay G. H. , du Boulay B. , Sharples M. , Teather D. 
Published: March 2018

Abstract:Radiological interpretation and diagnosis involves the comparison and classification of complex medical images and is typical of the categorisation tasks that have been the subject of observational studies in Cognitive Science. This paper considers the affinity between statistical modelling and theories of categorisation for naturally occurring categories. Statistical based measures of similarity and typicality with a probabilistic interpretation are derived. The utilisation of these measures in the support of diagnosis under uncertainty via interactive overview plots is described. The application of the methodology to magnetic resonance imaging of the head is considered. The methods detailed have application to other fields involving archiving and retrieving of image data.
Quantitative Blood Velocity Mapping in Glomerular Capillaries by in vivo Observation with an Intravital Videomicroscope
Authors: Takehara K. , Yamamoto T. , Hashimoto R. , Nakamoto H. , Kajiya F. , Ogasawara Y. 
Published: March 2018

Abstract:We have evaluated rat glomerular microcirculation under in-vivo condition with an intravital videomicroscope. To measure erythrocyte velocities, a line segment was set along the glomerular capillaries in time-sequential videotaped images and then a spatiotemporal image was constructed along that segment. The angle of striped pattern in the spatio-temporal image which reflects the erythrocyte velocity, was estimated to compute erythrocyte velocity vector mapping. We found that erythrocyte velocities in rat glomeruli were significantly faster in diabetic rats than in control rats (p <0.05). In conclusion, we have succeeded in quantitatively evaluating the in-vivo renal microcirculation with our videomicroscope system and by spatiotemporal image analyzing method.
Spatial Filtering Methods for Local Activation Determination in Fractionated Electrograms from Simulated Infarcted Hearts
Authors: Maglaveras N. , de Bakker J. , van Capelle F. J. L. , Pappas C. , Chouvarda I. 
Published: March 2018

Abstract:The purpose of this work is the enhancement of local activation in multiphasic extracellular recordings coming from infarcted myocardial tissue and, consequently, the distinction of local from distal activation. Deconvolution procedures are applied, in the form of spatial filtering, in order to estimate transmembrane currents from the extracellular recordings. Simulated data are used in order to test the methods. The current source estimates are compared to the actual transmembrane currents and to Laplacian estimates.