bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automatic Paroxysmal Atrial Fibrillation Based on not Fibrillating ECGs
Authors: Mota S. , Toro F. J. , Díaz A. F. , Fernández F. J. , Ros E. 
Published: March 2018

Summary

Objectives:
The objective of the paper is to describe an automatic algorithm for Paroxysmal Atrial Fibrillation (PAF) Detection, based on parameters extracted from ECG traces with no atrial fibrillation episode. The modular automatic classification algorithm for PAF diagnosis is developed and evaluated with different parameter configurations.

Methods:
The database used in this study was provided by Physiobank for The Computers in Cardiology Challenge 2001. Each ECG file in this database was translated into a 48 parameter vector. The modular classification algorithm used for PAF diagnosis was based on the nearest K-neighbours. Several configuration options were evaluated to optimize the classification performance.

Results:
Different configurations of the proposed modular classification algorithm were tested. The uni-parametric approach achieved a top classification rate value of 76%. A multi-parametric approach was configured using the 5 parameters with highest discrimination power, and a top classification rate of 80% was achieved; different functions to typify the parameters were tested. Finally, two automatic parametric scanning strategies, Forward and Backward methods, were adopted. The results obtained with these approaches achieved a top classification rate of 92%.

Conclusions:
A modular classification algorithm based on the nearest K-neighbours was designed. The classification performance of the algorithm was evaluated using different parameter configurations, typification functions and number of K-neighbors. The automatic parametric scanning techniques achieved much better results than previously tested configurations.
Accurate Volumetric Measurements of Anatomical Cavities
Authors: Orman J. , Gürvit Ö. , Bartz D. 
Published: March 2018

Summary

Objectives:
The volumetric assessment of anatomical cavities is of high relevance for various applications in medicine. Based on 3D scanning (i.e., CT) of these cavities, the volume can be determined by counting the volume elements of a segmentation of that cavity. Unfortunately, elements on the boundary of the segmentation require special treatment to obtain accurate volumetric measurements. In this paper, we propose a novel technique that in particular increases the accuracy of the volume estimation for the boundary elements of segmented anatomical objects.

Methods:
Based on a 3D segmentation of an anatomical cavity, we recursively subdivide boundary volume elements into a set of simple situations, where the volume can be estimated easily.

Results:
We performed volumetric measurements on seven datasets of phantom models made of plexiglass (see Fig. 1) scanned by a biplane angiography unit and assessed the quality of our method by comparing the measured volume by our novel method and by the fluid required to fill the phantom cavities.

Conclusions:
Our method calculates a significantly more accurate volume of the segmented cavities than previous methods. Nevertheless, it is only slightly more computationally expensive.
Sample Size Calculations for Controlled Clinical Trials Using Generalized Estimating Equations (GEE)
Authors: Rochon J. , König I. R. , Ziegler A. , Dahmen G. 
Published: March 2018

Summary

Objectives:
Clinical trials with correlated response data based on generalized estimating equations (GEE) have become increasingly popular as they require smaller samples than classical methods that ignore the clustered nature of the data. We have recently derived the recommendation to use the independence estimating equations (IEE) as primary analysis in most controlled clinical trials instead of GEE with estimated correlations [1]. Although several approaches for sample size and power calculation have been proposed, we have shown that most of these procedures are very specific and not as general as required for designing clinical trials.

Methods:
We extended the previously developed SAS macro GEESIZE to overcome this restriction. Specifically, we have added the option of an independence working correlation matrix required for the IEE. Additionally, we have reformulated the hypotheses to allow for coding that includes an intercept term instead of the previously used analysis of variance coding.

Results:
To demonstrate the validity of GEESIZE we investigate the calculated sample sizes for specific models where closed formulae are available. For illustration, we utilize GEESIZE for planning a new trial on the treatment of hypertension and thereby exemplify its flexibility.

Conclusions:
We show that our freely available macro is a very general and useful tool for sample size calculation purposes in clinical trials with correlated data.
A Simulation Model for Small-area Cancer Incidence Rates
Authors: Daugs A. , Meyer M. , Radespiel-Tröger M. 
Published: March 2018

Summary

Objectives:
Cancer epidemiologists are often asked by members of the interested public about possible associations between suspected carcinogens and apparently increased small-area cancer incidence rates. Frequently, no systematic incidence differences can be demonstrated. Nevertheless, it is necessary to address public concerns about suspected cancer clusters. To facilitate explanations about the large random variation of small-area tumor incidence, we implemented a software simulation tool in R.

Methods:
Under the assumption of no cancer causes other than chance, the tool simulates a small village population with an average number of five inhabitants per house and allows graphical visualisation of ten streets with 100 houses. Published age-specific incidence and mortality data are used for event sampling based on the binomial distribution. Program parameters include sample size, age distribution, cancer incidence, and mortality rates.

Results:
On average, 22 percent (2.2/10) of all houses per street have been inhabited by at least one cancer patient during the last five years in our simulated small village. A situation where all (10) houses in a street have been inhabited by at least one cancer patient during the last five years appears to be very rare (less than one in a million streets).

Conclusions:
Our software tool can be used effectively for numerical and graphical visualisation of small-area tumour incidence and prevalence rates due to chance alone. The explanation of basic epidemiological concepts to members of the public can help to increase public motivation and support for population-based cancer registration. Our simulation tool can be used to support this goal.
Annoyance from Multiple Transportation Noise: Statistical Models and Outlier Detection
Authors: Schürmann C. , Griefahn B. , Kuhnt S. 
Published: March 2018

Summary

Objective:
Statistical models for the annoyance from multiple transportation noise are needed to understand and predict the annoyance resulting from specific noise exposures.

Methods:
Models from the class of generalized linear models are suggested and discussed. Observations which are not well explained by the considered model are regarded as outliers. Outlier detection methods are applied to the data modelled by robust estimates using different link functions.

Results:
The discussed methods are applied to data from a laboratory experiment using generalized linear models. While considering outliers, a generalized linear model with a complementary log-log link is found to be a good choice in modelling the exposure-response relationship between noise levels and annoyance.
An Implementation of Automated Individual Matching for Observational Studies
Authors: Hüsing J. , Jöckel K.-H. , Schröder M. 
Published: March 2018

Summary

Objectives:
Individual matching is frequently used in observational studies. Its main purpose lies in efficiency of study conduct and parameter estimation. Ideally, an individually matched index subject differs from the reference subject(s) only by the factor(s) of interest. Matching is used to select comparable subgroups on which further data analysis can then concentrate. Finding optimal subsets is then a closed problem, which may include a lot of guesswork. It is a task that begs an algorithmic solution that can be obtained automatically.

Methods:
The problem can be formalized as a minimization of a global loss function that summarizes the deviation from perfect agreement over different variables. Through the representation by a network formed by a bipartite graph of index and reference subjects, one can obtain a solution by finding a minimum cost flow in a certain network. We have implemented a Web-based application using the efficient CS2 algorithm.

Results:
Variations of the individual matching procedures that have been implemented comprise 1:N matching and matching with a variable number of controls. The user can upload own data, view the proposed result in a list and finally download the matching plan. Representation of quality of individual matches as background colors allows rapid checks for overall matching accuracy.

Conclusions:
The computer-assisted variation reduces the human interaction to the tuning of a few parameters, rather than individual decisions on forming separate matches. This not only saves a lot of work but also simplifies communicating the matching process. The program addresses a general class of matching problems. The use of this tool for special cases of matching, as caliper matching or exact category matching, is highlighted.
Gene Methylation Data – a New Challenge for Bioinformaticians?
Authors: Müller H. M. , Fiegl H. , Widschwendter M. , Goebel G. 
Published: March 2018

Summary

Objectives:
Changes in the status of DNA methylation, known as epigenetic alterations, are among the most common molecular alterations in human neoplasia. For the first time, we reported on the analysis of fecal DNA from patients with CRC to determine the feasibility, sensitivity and specificity of this approach. We want to present basic information about DNA methylation analysis in the context of bioinformatics, the study design and several statistical experiences with gene methylation data. Additionally we outline chances and new research questions in the field of DNA methylation.

Methods:
We present current approaches to DNA methylation analysis based on one reference study. Its study design and the statistical analysis is reflected in the context of biomarker development. Finally we outline perspectives and research questions for statisticians and bioinformaticians.

Results:
Identification of at least three genes as potential DNA methylation-based tumor marker genes (SFRP2, SFRP5, PGR).

Conclusions:
DNA methylation analysis is a rising topic in molecular genetics. Gene methylation will push the extension of biobanks to include new types of genetic data. Study design and statistical methods for the detection of methylation biomarkers must be improved. For the purpose of establishing methylation analysis as a new diagnostic/prognostic tool the adaptation of several approaches has become a challenging field of research activity.
On Exemplary Scientific Conduct Regarding Submission of Manuscripts to Biomedical Informatics Journals
Authors: Groth T. , Hasman A. , Safran C. , Shortliffe E. H. , Haux R. , McCray A. T. , Miller R. A. 
Published: March 2018

SummaryAs the Editors of leading international biomedical informatics journals, the authors report on a recent pattern of improper manuscript submissions to journals in our field. As a guide for future authors, we describe ethical and pragmatic issues related to submitting work for peer-reviewed journal publication. We propose a coordinated approach to the problem that our respective journals will follow. This Editorial is being jointly published in the following journals represented by the authors: Computer Methods and Programs in Biomedicine, International Journal of Medical Informatics, Journal of Biomedical Informatics, Journal of the American Medical Informatics Association, and Methods of Information in Medicine.
Mapping OpenSDE Domain Models to SNOMED CT
Authors: Baofen Ding , Weeber M. , van Ginneken A. M. , Min Zhu 
Published: March 2018

Summary

Objectives:
To explore the strengths and pitfalls of mapping structured EPR (electronic patient record) terms (OpenSDE) to SNOMED codes.

Methods:
The OpenSDE model was developed for cardiovascular diseases in the context of the I4C project. We employed 35 patient records as references to adjust the model. We then performed automated and manual matches following the design of matching terms in the thesaurus of the resulting OpenSDE domain model to SNOMED concepts. Subsequently, we assessed what number of OpenSDE terms within the domain model can be matched to SNOMED concepts.

Results:
The OpenSDE domain tree contains 3230 nodes, involving 689 unique terms (terms can be associated with more than one node in different parts of a domain model tree). After final manual work for the 689 tree terms, 616 resulted in a good match, 31 in a partial match, and 42 in no match. Of the good matches, 23 produced multiple matches. The matches were used to represent the mapping of each node in the domain tree by concatenation of the matching terms.

Conclusions:
Mapping predefined terms in OpenSDE domain models to SNOMED Clinical Terms (CT) concepts eliminates laborious mapping for each individual patient record. The assignment of SNOMED codes to OpenSDE tree nodes facilitates exchange, aggregation, and research involving patient data. The mapping will serve the construction of queries at higher semantic levels than explicitly modeled in an OpenSDE domain model. However, the usefulness of the mapping result depends on the completeness of the mapping to SNOMED CT, for which there is no gold standard.
A Scoring System for Ascertainment of Incident Stroke; the Risk Index Score (RISc)
Authors: Moyé L. A. , Smith M. A. , Morgenstern L. B. , Kass-Hout T. A. 
Published: March 2018

Summary

Objectives:
The main objective of this study was to develop and validate a computer-based statistical algorithm that could be translated into a simple scoring system in order to ascertain incident stroke cases using hospital admission medical records data.

Methods:
The Risk Index Score (RISc) algorithm was developed using data collected prospectively by the Brain Attack Surveillance in Corpus Christi (BASIC) project, 2000. The validity of RISc was evaluated by estimating the concordance of scoring system stroke ascertainment to stroke ascertainment by physician and/or abstractor review of hospital admission records.

Results:
RISc was developed on 1718 randomly selected patients (training set) and then statistically validated on an independent sample of 858 patients (validation set). A multivariable logistic model was used to develop RISc and subsequently evaluated by goodness-of-fit and receiver operating characteristic (ROC) analyses. The higher the value of RISc, the higher the patient’s risk of potential stroke. The study showed RISc was well calibrated and discriminated those who had potential stroke from those that did not on initial screening.

Conclusion:
In this study we developed and validated a rapid, easy, efficient, and accurate method to ascertain incident stroke cases from routine hospital admission records for epidemiologic investigations. Validation of this scoring system was achieved statistically; however, clinical validation in a community hospital setting is warranted.
PACS Development in Austria: A Discussion of Success Criteria and Success Factors
Authors: Gell G. 
Published: March 2018

Summary

Objectives:
The paper uses the example of PACS (Picture Archiving and Communication System) in Austria (where some of the earliest large PACS projects were realised and led to a high penetration with state-wide networked PACS installations) to discuss success criteria and success factors of medical information systems.

Methods:
The paper describes the development of digital imaging in medicine and classifies the impact of systems according to their first or second order effects on patient care. The historic goals of PACS and the technical infrastructure in the eighties are shortly described.The paper then outlines the early PACS projects in Austria and their different approaches as well as the present state of PACS in Austria.

Results:
After giving a definition of success, success criteria (which allow to decide whether a system is in fact a success or not) are discussed in general – the final criterion being routine use – and in detail and it is concluded that PACS in Austria was and is indeed successful.

Conclusion:
The analysis of success factors shows a multitude of influences but the most decisive ones are the practical ability of the system to deliver a real service to health care and the ability to support the (key) users in their work and goals.
Implementation of Health Information Systems in Romania
Authors: Bazavan M. , Farcas D. D. , Mihalas G. I. 
Published: March 2018

Summary

Objectives:
The paper aimed to present and analyze the development of Healthcare Information Systems in Romania during the last decade. The first part was dedicated to the analysis of a large national project, HMIS – Healthcare Management Information System, and the second to the current state of the hospital information systems and primary care systems.

Methods:
The approach of a “case study” was used. The description of the HMIS project comprised the objectives and its structure, implementation, results and lessons learned. This is followed by a classical short presentation of the current state at the hospital and primary care levels.

Results:
The very modest results of the HMIS project were critically analyzed, listing the ‘failure factors’ at various moments, both weak points of the project as well as the consequences of the structural-organizational changes within the Romanian healthcare system during the implementation. However, mainly positive results were registered in the last years at lower levels, hospitals and primary care, which can also partially be interpreted as ‘lesson learned’.

Conclusions:
There are several things to be learned from the Romanian experience. Healthcare information system analysis is quite complex. Obtaining better results requires several additional measures including better education and training, adopting standards and appropriate quality assessment tools.
Standardized Exchange of Clinical Documents
Authors: Müller S. , Jablonski S. , Prokosch H.-U. , Gerdsen F. 
Published: March 2018

Summary

Objectives:
The exchange of medical data from research and clinical routine across institutional borders is essential to establish an integrated healthcare platform. In this project we want to realize the standardized exchange of medical data between different healthcare institutions to implement an integrated and interoperable information system supporting clinical treatment and research of glaucoma.

Methods:
The central point of our concept is a standardized communication model based on the Clinical Document Architecture (CDA). Further, a communication concept between different health care institutions applying the developed document model has been defined.

Results:
With our project we have been able to prove that standardized communication between an Electronic Medical Record (EMR), an Electronic Health Record (EHR) and the Erlanger Glaucoma Register (EGR) based on the established conceptual models, which rely on CDA rel.1 level 1 and SCIPHOX, could be implemented. The HL7-tool-based deduction of a suitable CDA rel.2 compliant schema showed significant differences when compared with the manually created schema. Finally fundamental requirements, which have to be implemented for an integrated health care platform, have been identified.

Conclusions:
An interoperable information system can enhance both clinical treatment and research projects. By automatically transferring screening findings from a glaucoma research project to the electronic medical record of our ophthalmology clinic, clinicians could benefit from the availability of a longitudinal patient record. The CDA as a standard for exchanging clinical documents has demonstrated its potential to enhance interoperability within a future shared care paradigm.
A CORBA-Based Object Framework with Patient Identification Translation and Dynamic Linking
Authors: Ohe K. , Wang C. 
Published: March 2018

Abstract:Exchanging and integration of patient data across heterogeneous databases and institutional boundaries offers many problems. We focused on two issues: (1) how to identify identical patients between different systems and institutions while lacking universal patient identifiers; and (2) how to link patient data across heterogeneous databases and institutional boundaries. To solve these problems, we created a patient identification (ID) translation model and a dynamic linking method in the Common Object Request Broker Architecture (CORBA) environment. The algorithm for the patient ID translation is based on patient attribute matching plus computer-based human checking; the method for dynamic linking is temporal mapping. By implementing these methods into computer systems with help of the distributed object computing technology, we built a prototype of a CORBA-based object framework in which the patient ID translation and dynamic linking methods were embedded. Our experiments with a Web-based user interface using the object framework and dynamic linking through the object framework were successful. These methods are important for exchanging and integrating patient data across heterogeneous databases and institutional boundaries.
Computer-Supported Diagnosis of Melanoma in Profilometry
Authors: Roß Th. , Kreusch J. , Wolff H. H. , Pöppl S. J. , Handels H. 
Published: March 2018

Abstract:Laser profilometry offers new possibilities to improve non-invasive tumor diagnostics in dermatology. In this paper, a new approach to computer-supported analysis and interpretation of high-resolution skin-surface profiles of melanomas and nevocellular nevi is presented. Image analysis methods are used to describe the profile‘s structures by texture parameters based on co-occurrence matrices, features extracted from the Fourier power spectrum, and fractal features. Different feature selection strategies, including genetic algorithms, are applied to determine the best possible subsets of features for the classification task. Several architectures of multilayer perceptrons with error back-propagation as learning paradigm are trained for the automatic recognition of melanomas and nevi. Furthermore, network-pruning algorithms are applied to optimize the network topology. In the study, the best neural classifier showed an error rate of 4.5% and was obtained after network pruning. The smallest error rate in all, of 2.3%, was achieved with nearest neighbor classification.
A Computer-Assisted Drug Prescription System: the Model and its Implementation in the ATM Knowledge Base
Authors: Pouliquen B. , Le Beux P. , Riou C. 
Published: March 2018

Abstract:Informatisation of drug prescription is an important topic in medical informatics. For several years now, computerized drug databases have been implemented. Usually only a small part of the prescriptions can be stored in prescription systems because of the format of the included information; prescriptions contain essentially free text without any structure and homogeneity of the used vocabulary.In this article a model is presented for knowledge representation in a computerized drug prescription system. The model should be applicable to clinical practice and be didactic for medical students. The problem of standardization of terminology had to be solved. A computer-assisted drug prescription program has been developed. The next step is its validation by clinicians. The program can also be used in a consultation mode.