bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Semantic Approach to Segmentation of Overlapping Objects
Authors: Grobe M. , Münzenmayer C. , Kuziela H. , Spinnler K. , Wittenberg T. 
Published: March 2018

Summary

Objectives:
This paper aims at introducing a novel approach for segmentation of overlapping objects and at demonstrating its applicability to medical images.

Methods:
This work details a novel approach enhancing the known theory of full-segmentation of an image into regions by lifting it to a semantic segmentation into objects. Our theory allows the formal description of partitioning an image into regions on the first level and allowing the occurrence of overlaps and occlusions of objects on a second, semantic level. Possible applications for the use of this ‘semantical segmentation‘ are the analysis of radiographs and micrographs. We demonstrate our approach by the example of segmentation and separation of overlapping cervical cells and cell clusters on a set of 787 image pairs of registered PAP- and DAPI-stained micrographs. The semantical cell segmentation yielding areas of cell plasmas and nuclei are compared to a manual segmentation of the same images, where 2212 cells have been labeled. A direct comparison of over and under-segmentation between the two segmentation sets yields a mean difference value of 10.15% for the nuclei and 10.80% for the plasma.

Results:
Using the proposed theory of semantical segmentation of images in combination with adequate models of the image contents, our approach allows identifying, separating and distinguishing several overlapping, occluding objects in medical images. Applying the proposed theory to the application of cervical cell segmentation from overlapping cell clusters and aggregates, it can be seen that it is possible to formally describe the complex image contents.

Conclusions:
The proposed method of semantical segmentation is a mighty tool and under the assumption of the subtractive transparency model can be used in different medical image processing applications such as radiology and microscopy. By using alternative models to solve the ambiguities attached to overlaps and occlusions, further fields of application can be addressed.
Comparison of Preprocessing Procedures for Oligo-nucleotide Micro-arrays by Parametric Bootstrap Simulation of Spike-in Experiments
Authors: Freudenberg J. , Boriss H. , Hasenclever D. 
Published: March 2018

Summary

Objective:
Due to scarcity of calibration data for micro-array experiments, simulation methods are employed to assess preprocessing procedures. Here we analyze several procedures’ robustness against increasing numbers of differentially expressed genes and varying proportions of up-regulation.

Methods:
Raw probe data from oligo-nucleotide micro-arrays are assumed to be approximately multivariate normally distributed on the log scale. Chips can be simulated from a multivariate normal distribution with mean and variance-covariance matrix estimated from a real raw data set.A chip effect induces strong positive correlations. In reverse, sampling from a normal distribution with strong correlation variance-covariance matrix generates data exhibiting a chip effect. No explicit model of chip-effect is needed. Differences can be artificially spiked-in according to a given distribution of effect sizes.Thirty preprocessing procedures combining background correction, normalization, perfect match correction and summarization methods available from the BioConductor project were compared.

Results:
In the symmetrical setting “50% differentially expressed genes, 50% of which up-regulated” background correction reduces bias, but inflates low intensity probe variance as well as the mean squared error of the estimates. Any normalization reduces variance and increases sensitivity with no clear winner. Asymmetry between up and down regulation causes bias in the effect-size estimate of non-differentially expressed genes. This markedly inflates the false positive discovery rates. Variance stabilizing normalization (VSN) behaved best.

Conclusion:
A simple parametric bootstrap was used to simulate oligo-nucleotide micro-array raw data. Current normalization methods inflate the false positive rate when many genes show an effect in the same direction.
Correcting the QT Interval for Changes in HR in Pre-clinical Drug Development
Authors: Markert M. , Meyners M. 
Published: March 2018

Summary

Objectives:
Estimation of possible cardiovascular side effects belongs to the safety assessment of every drug candidate. Drug-induced prolongation of the QT interval can result in life-threatening ventricular arrhythmia. In pre-clinical drug development, animal experiments are used to study this possible effect. Researchers have become aware that correction formulae derived for human beings are not applicable to animal experiments.

Methods:
We investigated some of the proposed models by comparing the outcomes of the analyses on the same data. The data was derived from telemetry measurements on Labrador dogs. We propose the use of both the correlation with heart rate (or RR interval) and a measure of predictive performance. As a sufficiently large number of observations were available, the data was subdivided into a training and a test set. The training set serves to estimate the respective parameters while the test set is used to determine the performance of the model. Here, a kind of PRESS statistic was used. Next, the models were considered for treated animals, using the estimated parameters. Both positive and negative controls were used.

Conclusions:
Most models under consideration performed quite well. These models eliminated the correlation for the most part and were reasonably predictive. Furthermore, they reliably differentiate between positive and negative controls. The next steps in identifying the best correction will be to consider additional compounds as well as other species to validate our current results.
Simultaneous Confidence Intervals for Ratios with Applications to the Comparison of Several Treatments with a Control
Authors: Bretz F. , Guiard V. , Hothorn L. A. , Dilba G. 
Published: March 2018

Summary

Objectives:
In this article, we illustrate and compare exact simultaneous confidence sets with various approximate simultaneous confidence intervals for multiple ratios as applied to many-to-one comparisons. Quite different datasets are analyzed to clarify the points.

Methods:
The methods are based on existing probability inequalities (e.g., Bonferroni, Slepian and Šidàk), estimation of nuisance parameters and re-sampling techniques. Exact simultaneous confidence sets based on the multivariate t-distribution are constructed and compared with approximate simultaneous confidence intervals.

Results:
It is found that the coverage probabilities associated with the various methods of constructing simultaneous confidence intervals (for ratios) in many-to-one comparisons depend on the ratios of the coefficient of variation for the mean of the control group to the coefficient of variation for the mean of the treatments. If the ratios of the coefficients of variations are less than one, the Bonferroni corrected Fieller confidence intervals have almost the same coverage probability as the exact simultaneous confidence sets. Otherwise, the use of Bonferroni intervals leads to conservative results.

Conclusions:
When the ratio of the coefficient of variation for the mean of the control group to the coefficient of variation for the mean of the treatments are greater than one (e.g., in balanced designs with increasing effects), the Bonferroni simultaneous confidence intervals are too conservative. Therefore, we recommend not using Bonferroni for this kind of data. On the other hand, the plug-in method maintains the intended confidence coefficient quite satisfactorily; therefore, it can serve as the best alternative in any case.
Some Problems with the Investigation of Noninferiority in Meta-analysis
Authors: Victor N. , Witte S. 
Published: March 2018

Summary

Objectives:
Noninferiority trials have become commonplace in recent years. Like individual clinical trials, meta-analyses can also investigate noninferiority. However, certain important topics have to be considered.

Methods:
The proposed methods in this paper have their origin in the framework of noninferiority trials and meta-analyses. This paper can therefore be seen as a combination of both fields. Two issues are highlighted in the paper; difficulties in the choice of delta for a noninferiority meta-analysis leading to different deltas and methods for meta-analyses with different analysis sets, based on the full-analysis set with the intention-to-treat principle or the per-protocol population. Analytical methods, sensitivity analyses, meta-regression, and a bivariate method are introduced. The proposed graphical presentations support the analytical results.

Conclusion:
The confidence interval approach using meta-regression or bivariate methods is appropriate using both analysis sets for meta-analyses investigating noninferiority.
Determination of the Population Size
in an Epidemiological Study with Children
Authors: Forster J. , Petersen G. , Schumacher M. , Ihorst G. 
Published: March 2018

Summary

Objectives:
To obtain a reliable estimate of the population size in an epidemiological study concerned with incidence estimation.

Methods:
In the present case, the population of interest consists of all children attending a certain pediatric practice for any reason and is estimated making use of the number of regularly attended well baby visits. In some cases, exact figures from the practices are available as a reference. A prospective epidemiological study on the estimation of the incidence of lower respiratory tract infections (LRTI) in the German pediatric population (PRI.DE, Parainfluenza- und Respiratory-Syncytial-Virus-Infektionen in Deutschland) is used to demonstrate the procedure.

Results:
In most cases, the fit can be regarded as good with deviations between 11% and 17%, whereas in a few cases it must be considered as poor (deviations of 60%).

Conclusions:
The importance of using exact figures whenever obtainable and of appraising the results carefully is emphasized.
Using Mandatory Data Collection on Multiresistant Bacteria for Internal Surveillance in a Hospital
Authors: Mikolajczyk R. T. , Krämer A. , Sagel U. 
Published: March 2018

Summary

Objectives:
Multiresistant pathogens cause major clinical problems and considerably increase treatment costs. Since 2001 the Protection Against Infection Act (PIA) obligates hospitals in Germany to the documentation of multiresistant bacteria. We analyzed the use of these data for routine internal surveillance.

Methods:
We used standard data collected for the mandatory documentation and studied consecutive diagnoses of Methicillin-resistant Staphylococcus aureus (MRSA) in a 893-bed tertiary level hospital in North Rhine-Westphalia in Germany. Based on the Poisson distribution for the cumulative yearly incidence of MRSA, we defined a threshold level for an outbreak.

Results:
During a 12-month time period 80 patients were diagnosed with MRSA. The time structure and spatial distribution of different MRSA phenotypes (defined through specific antibiotic resistance patterns) were consistent with the within-hospital transmission. In the two preceding time periods of 12 months each, 15 respectively 8 patients with MRSA were found. The defined alert threshold level for cumulative yearly incidence was crossed in the beginnings of the outbreak.

Conclusion:
Monitoring the mandatory data collected on multiresistant bacteria allows the early detection of accumulations suspect for the within-hospital transmission. This knowledge can be used for a fast reaction and breaking off the transmission chains.
Knowledge and Process Management in Health Care Organizations
Authors: Stefanelli M. 
Published: March 2018

Summary

Objective:
Medical knowledge management and care process management have become to be considered as valuable strategic assets that can lead to sustained increase in Health Care Organization (HCO) performance. Thus, it is essential to investigate which are the enablers for promoting knowledge-based organizations (people, organization, process, and system perspectives). Although they are essential for a HCO to manage knowledge effectively, it is still unclear how to employ them in more principled fashion. This requires innovative management strategies to determine effective ways of utilizing knowledge resources and capabilities available both within and outside the organization.

Method:
This paper reviews knowledge and process management theories, methods, and technologies that are potentially effective in building high performance HCOs. They come from a variety of fields behind computer science and medical informatics, e.g. from business and organization sciences to psychological and cognitive sciences, from epistemology to sociology. However, the success in developing future Health Information Systems (HIS) requires their incorporation into a new conceptual framework after recognizing how peculiar are the characteristics of HCOs with respect to other organizations. Investigating the nature of knowledge, in general, and of medical knowledge, in particular, is essential to define which services the future HIS should provide to foster collaboration between patients and health professionals. The knowledge creation process is then described in order to emphasize its dynamic and social characteristics. The potential of workflow technology for building innovative HISs is analyzed together with several basic research issues which are very challenging for researchers in the field.

Result:
A framework for augmenting the conceptual analysis of theories, methods, tools and effects of knowledge management in building high performance HCOs.
Selected Impressions on the Beginning of the Electronic Medical Record and Patient Information
Authors: Klar R. 
Published: March 2018

Summary

Objectives:
To present an overview of early European and American work on Electronic Medical Records and patient information.

Method:
The invited lectures of “pioneers of electronic patient information” given at the farewell symposium of Wolfgang Giere in Frankfurt, Germany, are summarized and discussed.

Results:
The origin of medical record writing goes back to Hippocrates and over many centuries this important medical duty was regarded as an annoying, laborious and error-prone task. First steps towards a better medical record started in 1936 with punch cards. In the 1960s the minimum basic data set, a unique patient ID was introduced and even for outpatients first com-puterized medical record systems were developed applying some important standards and well accepted data structures. Nowadays multimedia are included in patient record systems, highly specialized subsystems e.g. for radiology or cardiology are available, and semantic and statistic mining techniques as well as medical classifications and standardized terminologies support evaluation. All these methods should primarily improve the quality of care, reduce errors, improve communication between multiple specialists, reduce wait times for patients and improve efficiency.

Conclusions:
Over decades it became obvious that the structure of a medical record notably for coded data but also for narrative text and pictures must be carefully modelled. Well maintained standardized health terminologies and medical classifications are important issues for a user-friendly electronic medical record, which bring benefits for clinicians and patients.
A Terminological and Ontological Analysis of the NCI Thesaurus
Authors: Smith B. , Goldberg L. , Ceusters W. 
Published: March 2018

Summary

Objective:
The National Cancer Institute Thesaurus is described by its authors as “a biomedical vocabulary that provides consistent, unambiguous codes and definitions for concepts used in cancer research” and which “exhibits ontology-like properties in its construction and use”. We performed a qualitative analysis of the Thesaurus in order to assess its conformity with principles of good practice in terminology and ontology design.

Materials and Methods:
We used both the on-line browsable version of the Thesaurus and its OWL-representation (version 04.08b, released on August 2, 2004), measuring each in light of the requirements put forward in relevant ISO terminology standards and in light of ontological principles advanced in the recent literature.

Results:
We found many mistakes and inconsistencies with respect to the term-formation principles used, the underlying knowledge representation system, and missing or inappropriately assigned verbal and formal definitions.

Conclusion:
Version 04.08b of the NCI Thesaurus suffers from the same broad range of problems that have been observed in other biomedical terminologies. For its further development, we recommend the use of a more principled approach that allows the Thesaurus to be tested not just for internal consistency but also for its degree of correspondence to that part of reality which it is designed to represent.
A Signal Processing Pipeline for Noninvasive Imaging of Ventricular Preexcitation
Authors: Hanser F. , Pfeifer B. , Seger M. , Hintermüller C. , Modre R. , Tilg B. , Trieb T. , Berger T. , Roithinger F. X. , Hintringer F. , Fischer G. 
Published: March 2018

Summary

Objectives:
Noninvasive imaging of the cardiac activation sequence in humans could guide interventional curative treatment of cardiac arrhythmias by catheter ablation. Highly automated signal processing tools are desirable for clinical acceptance. The developed signal processing pipeline reduces user interactions to a minimum, which eases the operation by the staff in the catheter laboratory and increases the reproducibility of the results.

Methods:
A previously described R-peak detector was modified for automatic detection of all possible targets (beats) using the information of all leads in the ECG map. A direct method was applied for signal classification. The algorithm was tuned for distinguishing beats with an adenosine induced AV-nodal block from baseline morphology in Wolff-Parkinson-White (WPW) patients. Furthermore, an automatic identification of the QRS-interval borders was implemented.

Results:
The software was tested with data from eight patients having overt ventricular preexcitation. The R-peak detector captured all QRS-complexes with no false positive detection. The automatic classification was verified by demonstrating adenosine-induced prolongation of ventricular activation with statistical significance (p <0.001) in all patients. This also demonstrates the performance of the automatic detection of QRS-interval borders. Furthermore, all ectopic or paced beats were automatically separated from sinus rhythm. Computed activation maps are shown for one patient localizing the accessory pathway with an accuracy of 1 cm.

Conclusions:
The implemented signal processing pipeline is a powerful tool for selecting target beats for noninvasive activation imaging in WPW patients. It robustly identifies and classifies beats. The small beat to beat variations in the automatic QRS-interval detection indicate accurate identification of the time window of interest.
Evaluation of Health Information Applications – Challenges Ahead of Us
Authors: Brender J. 
Published: March 2018

Summary

Objectives:
The aim of the paper is to review the challenges for evaluation in the light of characteristics of the healthcare sector, present as well as future.

Methods:
The approach is a synthesis based on highlights from the literature.

Results:
The review addresses the following issues: 1) the role of evaluation activities within a systems development or implementation context; 2) suggestions on the nature of success and failure characteristics; and 3) evaluation aspects viewed in the perspective of different types of systems. Constructive evaluation, evaluation being the act of bringing about a decision-making basis, is perceived as the means to minimize failure and maximize success from the very beginning of the development or implementation. Based on these discussions, the challenges that evaluation and evaluators are facing are debated.

Conclusion:
The ultimate challenge ahead is first to fill the gap of presently needed evaluation methods. This need is in particular related to evaluation of cognitive and work process-oriented aspects of IT-based solutions. Finally, the challenge is to provide constructive evaluation methods and methodologies for dealing with the full complexity and dynamics of the target domain, for application within the entire life-cycle of the IT-based systems and solutions.
Lest Formalisms Impede Insight and Success: Evaluation in Health Informatics
Authors: Anglin C. , Schaafsma J. , Pantazi S. , Grimm N. , Moehr J. R. 
Published: March 2018

Summary

Objectives:
To illustrate the advantages of an open-ended formative evaluation approach using a project-specific selection of methods over the controlled trial approach in the evaluation of health information systems. To illustrate factors leading to success and others impeding it in a telehealth project.

Methods:
The methods and results of an evaluation of the BC Telehealth Program are summarized.

Results:
The evaluation gave a comprehensive picture of the project, including assessment of the effects of an array of telehealth applications, and their economic impact. Factors leading to success and others preventing it are identified from the level of overall program management to the project specifics. The results include unanticipated effects and explanations for their reasons of occurrence. Neither the comprehensiveness of information nor the timeliness was achieved in a related project using a controlled trial approach.

Conclusions:
Not all types of health information system projects can be evaluated using the controlled trial approach. This approach may impede important insights. It is also usually much less efficient. Funding agencies and journal editors have to take this into account when selecting projects for funding and submissions for publication.
Factors Influencing Success and Failure of Health Informatics Systems
Authors: Ammenwerth E. , Nykänen P. , Talmon J. , Brender J. 
Published: March 2018

Summary

Objectives:
The aim is to gain information on factors influencing success and failure for Health Informatics applications from a group of medical informaticians.

Methods:
Based on the presentations at a special topic conference on success and failure in Health ICT and analysis of the proceedings, we conducted a Delphi study on success and failure aspects.

Results:
A total of 110 success factors and 27 failure criteria were identified, distributed on categories like functional, organizational, behavioral, technical, managerial, political, cultural, legal, strategy, economy, education and user acceptance. These factors and criteria were rated for six different system types. Unanimously it was agreed that “collaboration and co-operation” and “setting goals and courses” are “essential for the success” of clinical systems, and “user acceptance” for educational systems. Similarly, the score “essential in order to avoid a failure” were given unanimously on clinical systems for “response rate and other performance measures” and on administrative systems for “not understanding the organizational context” with “not understanding or foreseeing the extent to which the new IT-system affects the organization, its structure and/or work procedures” as the highest scoring sub-item.

Conclusions:
All success factors and failure criteria were considered relevant by the Delphi expert panel. There is no small set of relevant factors or indicators, but success or failure of a Health ICT depends on a large set of issues. Further, clinical systems and decision support systems depend on more factors than other systems.