bluuebunny/crossref_metadata_2025_split huggingface dataset:
Digital Optical Archiving of Medical Records in Hospital Information Systems – A Practical Approach Towards the Computer-based Patient Record?
Authors: Dujat C. , Haux R. , Schmücker P. , Winter A. 
Published: March 2018

Abstract:The large number of inpatients and outpatients in university hospitals leads to high costs of medical documentation and to an increasing number of medical documents. Due to legal regulations, these medical records have to be stored for 30 years. This implies spatial, organizational, and economical problems. At present, conventional archiving in hospitals often does not satisfy the need to make medical records available for healthcare professionals in a systematic and timely manner. From 1989 to 1993 a pilot study on “digital optical archiving of medical records” was carried out at Heidelberg University Hospital. The study has shown the feasibility of digital optical archiving in hospitals if done under certain conditions. In 1995, Heidelberg University Hospital adopted a procedure for“ digital optical archiving of medical records”. The digital optical archive will first be filled with the medical records of the department of neurosurgery and the endoscopic and echographic images and reports of the department of internal medicine. It is to be expected that this procedure will gradually lead to an integrated functionality on health-care professional workstations, to a hospital-wide use of an electronic patient record, and to media-independent document management systems. The paper focusses on the potentials of digital optical archiving as an integral part of hospital information systems, and on the requirements for the systematic managements of hospital information systems with respect to digital optical archives.
A Method to Derive the Time of Onset of Infection from Serological Findings
Authors: Steimann F. , Hayde M. 
Published: March 2018

Abstract:Among the diagnostic problems requiring a retrospective assessment of the time an event occurred is that of screening for primary infection with Toxoplasma gondii acquired during pregnancy. We suggest a method to derive the possible times of onset of infection from a small sequence of serological samples by matching them against the knowledge about possible courses of infection. Special care is taken to properly address the relative change of consecutive samples, a nontrivial problem when reasoning about sparsely sampled time courses. To investigate the practicability of our approach we conducted a retrospective and a simulated prospective evaluation based on the samples of 394 pregnancies, randomly selected from our toxoplasmosis database; we could demonstrate an overall accuracy of 95.7%.
Study of Situation-dependent Clinical Cognition: a Meta-analysis and Preliminary Method
Authors: Westergren V. , Hallberg N. , Forsum U. , Timpka T. 
Published: March 2018

Abstract:An integrated method was constructed for the study of in situ clinical reasoning. A meta-analysis of existing theories and an exploratory case study were performed. Twelve physicians at the department of otorhinolaryngology, and three physicians and three biomedical technologists at the clinical microbiological laboratory of an 800-bed university hospital were involved in the evaluation of the method. The meta-analysis identified situations where practitioners face assignments for which they follow no routine strategy as suitable starting points for the development of the method, in which organizational processes are presented as workflow graphs. Using the critical incident technique, problem situations in the processes are identified, and stimulated recall interviews are employed to construct a model of the situation-dependent logic used in decision-making. The case study showed thatthe first levels of the method could easily be used by physicians without training in organizational development or cognitive psychology. It is concluded that the method can be a means for case construction in problem-oriented learning programs that have an empirical background. It can also be used in the development of clinical organization, where training is combined with the establishment of critical paths and computer support.
Adjusting for Recall Bias with the Proportional Hazards Model
Authors: Reinsch S. , MacRae P. G. , Tobis J. S. , Lachenbruch P. A. 
Published: March 2018

AbstractIn studying falling frequency in the elderly, we observed that having subjects keep a diary led to a larger number of falls reported than had been noted in a previous study in the same population. The previous study asked subjects to report any falls in the previous three months. We considered two related explanations for the observation of lower incidence reports with a 3-month recall survey. First, there may have been under-reporting of falls due to recall bias. Second, the less severe falls (which did not result in injuries) may not be reported. We suggest that the proportional hazards model may be used to adjust studies in which recall is used to determine incidence and time to falls.
Quantitative Evaluation of English-Japanese Machine Translation of Medical Literature
Authors: Kiuchi T. , Kaihara S. 
Published: March 2018

AbstractAlthough many machine-translation programs are currently available, few evaluation methods of such translation exist for any given application area. It is difficult to evaluate machine-translation systems objectively because the quality of a translation depends on the combination of three factors: the translation program, the dictionary, and the original document. In this study, we developed a quantitative evaluation method for assessing machine translation, which evaluates these three factors separately. We applied this method to the translation of English to Japanese for medical literature and the method proved to be a good indicator for further system improvement. Using this method we also discovered other important points for machine translation, such as the examination of target documents for the construction of a better application dictionary.
Record Linkage Strategies: Part II. Portable Software and Deterministic Matching
Authors: Roos L. L. , Layefsky M. , Singleton J. A. , Wajda A. 
Published: March 2018

AbstractSoftware to perform record linkage should have several characteristics: (1) portability in being able to function with researchers’ current arrangement of computer systems and languages, (2) flexibility in handling different linkage strategies, and (3) low cost in both computer time and researchers’ efforts. A linkage package (LINKS) is described which satisfies these criteria; LINKS provides tools for both deterministic and probabilistic linkage as well as test modules for assessing data quality and structure. Because each linkage project is different, the modular nature of the software allows for better control of the programming process and development of unique strategies. Since the user provides the weights and decision rules, he may modify data between steps and/or develop extra steps to supplement the basic modules. In two information-rich linkage projects involving California AIDS data, LINKS identified mortality using deterministic approaches and permitted comparisons with other software and strategies. Flexible software and a deterministic approach would have eliminated the expensive key entry used to add full names and social security numbers as additional identifiers to one of the California data files.
LIED - Liver: Information, Education and Diagnosis
Authors: Console L. , di Meana V. , Torasso P. , Molino G. 
Published: March 2018

Abstract:In this paper we describe LIED (Liver: Information, Education and Diagnosis), a diagnostic expert system devoted to medical education in the field of hepatology6. LIED combines the facilities of a traditional expert system for clinical diagnosis with several modules designed for educational purposes. The goal of such modules is to train physicians, in particular as regards the improvement of their problem solving ability (at the end of their curricula students in medicine usually lack experience in organizing an efficient and accurate diagnostic process). Training on real and simulated cases has been widely recognized as a proper approach to clinical experience. The architecture of the diagnostic system is introduced, which forms the core of LIED, and which has been derived from our previous experience, and the various educational functions are discussed that were developed on top of the basic architecture.
Checkup Interval and Cancers in Automated Multiphasic Health Testing and Services
Authors: Takahashi T. , Uemura H. , Noto T. , Shinozuka T. , Kinoshita H. , Matsuyama M. , Suzuki S. , Osamura Y. , Oogushi Y. , Hinohara S. 
Published: March 2018

Abstract:The purpose of this study was to disclose which types of cancer and how many persons with cancer were detected among the AMHTS examinees of our AMHTS center by using the hospital information retrieval system, and to study the relationship between cancer and the number of examinees, checkup intervals, and frequency in AMHTS. The examinees who had checkups more than twice were divided into three groups based on their checkup intervals: within one year, one to two years, and over two years. The relationship between cancer ratios and checkup intervals was evaluated in each group of examinees. In those having checkups within one year and from one to two years the cancer rate was 2.9 patients per 1,000 persons. However, in those having checkups after a two-year period or longer, the cancer rate was 4.3, clearly greater than the rate of the other two groups.
Intelligent Processing of Loosely Structured Documents as a Strategy for Organizing Electronic Health Care Records
Authors: Essin D. J. 
Published: March 2018

AbstractLoosely structured documents can capture more relevant information about medical events than is possible using today’s popular databases. In order to realize the full potential of this increased information content, techniques will be required that go beyond the static mapping of stored data into a single, rigid data model. Through intelligent processing, loosely structured documents can become a rich source of detailed data about actual events that can support the wide variety of applications needed to run a health-care organization, document medical care or conduct research. Abstraction and indirection are the means by which dynamic data models and intelligent processing are introduced into database systems. A system designed around loosely structured documents can evolve gracefully while preserving the integrity of the stored data. The ability to identify and locate the information contained within documents offers new opportunities to exchange data that can replace more rigid standards of data interchange.
A Model for Estimation of the Pulmonary Capillary Pressure
Authors: Jensen E. W. , Demant L. , Sanchez R. 
Published: March 2018

Abstract:To estimate the pulmonary capillary pressure, a theory was introduced by Holloway and coworkers. Based upon this, a mathematical model describing the measured data was developed. Because the physiologic data are embedded in noise and the pulmonary capillary pressure cannot be measured directly, we simulated an extensive series of data. The noise properties of the data were as analyzed to design a signal-processing tool, that cancels the noise from the measured data. The signal processing tool developed for the current application consists of pre-processing with a moving time average filter and post-processing with a neural network. After a verification procedure the tool can be applied to measured data, hence a more reliable measurement of the pulmonary capillary pressure is achieved.
Adaptive Signal Analysis and Interpretation for Real-time Intelligent Patient Monitoring
Authors: Manders E. J. , Lindstrom D. P. , Dawant B. M. 
Published: March 2018

Abstract:On-line intelligent monitoring, diagnosis, and control of dynamic systems such as patients in intensive care units necessitates the context-dependent acquisition, processing, analysis, and interpretation of large amounts of possibly noisy and incomplete data. The dynamic nature of the process also requires a continuous evaluation and adaptation of the monitoring strategy to respond to changes both in the monitored patient and in the monitoring equipment. Moreover, real-time constraints may imply data losses, the importance of which has to be minimized. This paper presents a computer architecture designed to accomplish these tasks. Its main components are a model and a data abstraction module. The model provides the system with a monitoring context related to the patient status. The data abstraction module relies on that information to adapt the monitoring strategy and provide the model with the necessary information. This paper focuses on the data abstraction module and its interaction with the model.
Bonhoeffer-van der Pol Oscillator Model of the Sino-Atrial Node: A Possible Mechanism of Heart Rate Regulation
Authors: Sato S. , Doi S. , Nomura T. 
Published: March 2018

Abstract:A Bonhoeffer-van der Pol equation with a stable limit cycle is proposed as a model of the pacemaker in the sino-atrial node to exptain heart rate regulation. Standard tools, such as the phase transition curve in nonlinear dynamic system theory, are used to analyze the model and results are compared with other studies on experiments with dogs.
Heart Signal Recognition by Hidden Markov Models: The ECG Case
Authors: Thoraval L. , Carrault G. , Bellanger J. J. 
Published: March 2018

Abstract:Wave recognition in ECG signals by Hidden Markov Models (HMMs) relies on the stationary assumption for the set of parameters used to describe ECG waves. This approach seems unnatural and consequently generates severe errors in practice. A new class of HMMs called Modified Continuous Variable Duration HMMs is proposed to account for the specific properties of the ECG signal. An application of the latter, coupled with a multiresolution front-end analysis of the ECG is presented. Results show these methods can increase the perfomance of ECG recognition compared to classical HMMs.
Neural Network for Automatic Analysis of Motility Data
Authors: Kruse-Andersen S. , Kolberg J. , Jakobsen E. 
Published: March 2018

Abstract:Continuous recording of intraluminal pressures for extended periods of time is currently regarded as a valuable method for detection of esophageal motor abnormalities. A subsequent automatic analysis of the resulting motility data relies on strict mathematical criteria for recognition of pressure events. Due to great variation in events, this method often fails to detect biologically relevant pressure variations. We have tried to develop a new concept for recognition of pressure events based on a neural network. Pressures were recorded for over 23 hours in 29 normal volunteers by means of a portable data recording system. A number of pressure events and non-events were selected from 9 recordings and used for training the network. The performance of the trained network was then verified on recordings from the remaining 20 volunteers. The accuracy and sensitivity of the two systems were comparable. However, the neural network recognized pressure peaks clearly generated by muscular activity that had escaped detection by the conventional program. In conclusion, we believe that neu-rocomputing has potential advantages for automatic analysis of gastrointestinal motility data.
Nonlinear Interpretation of Respiratory Sinus Arrhythmia in Anesthesia
Authors: Loula P. , Lipping T. , Jäntti V. , Yli-Hankala A. 
Published: March 2018

Abstract:A non-parametric method is presented for modelling nonlinear dynamic mechanisms of respiratory sinus arrhythmia (RSA) in anesthesia caused by positive pressure ventilation. RR interval sequences are shown with Tsay’s linearity test to contain both short-term and long-term nonlinear components, which cannot completely be modelled with optimal linear methods. The nonlinear approach is based on Wiener’s theory for broad-band random input signal. The input-output model is formed for tracheal pressure and RR interval sequence. Second-order and third-order nonlinearities in RSA fluctuation are found and demonstrated.
Reconstruction of Repetitive Signals
Authors: van Bemmel J. H. , Schijvenaars R. J. A. , Kors J. A. 
Published: March 2018

Abstract:A technique is presented for the reconstruction of signals that suffered sampling-frequency decimation. Two assumptions are made: the original signal has to be repetitive, and no anti-aliasing filter has been used before frequency decimation. The performance of the technique is assessed by using test signals of which the original signal is known.
Selective Averaging of Evoked Potentials using Trajectory-Based Clustering
Authors: Nyberg H. N. , Zouridakis G. , Jansen B. H. 
Published: March 2018

Abstract:A clustering method has been developed to group evoked potentials that display similar prestimulus dynamic behavior. The procedure involves using the method of time delay embedding to construct a trajectory in state space from a time series. Certain features that characterize the geometry of the trajectory have been defined. The trajectory-based clustering algorithm has been applied to visual evoked potentials to determine relationships between prestimulus EEG and evoked potential shape.
Parameters for a Knowledge Base for Acute Appendicitis
Authors: Ikonen J. , Juhola M. , Eskelinen M. , Pesonen E. 
Published: March 2018

Abstract:Acute appendicitis is the most common cause of acute abdomen requiring surgical intervention. The clinical diagnosis of acute appendicitis is not always easy due to variable symptomatology, particularly at the onset. The contributions of history-taking and physical examination in the diagnosis of acute appendicitis was studied in connection with the Research Committee of the World Organization of Gastroenterology (OMGE) survey of acute abdominal pain. Especially the suitability of diagnostic parameters in the construction of an expert system for automatic decision making was studied. The results clearly show that it is possible to construct an expert system for automatic decision making in the diagnosis of acute appendicitis.
Time-Frequency Analysis of Ventricular Late Potentials
Authors: Khadra L. , Brachmann J. , Dickhaus H. 
Published: March 2018

Abstract:The time-frequency characteristics are studied of averaged and filtered ECG records from 21 patients with sustained ventricular tachycardia and 29 healthy control subjects. Simulated data as well as real ECG records reveal the detection accuracy of the wavelet transform of signals with late potentials. The wavelet-transforms of preprocessed ECG signals are plotted in the time-frequency plane. These representations of the signals are well suited to describe the different characteristics of the patients and healthy subjects. A quantitative discrimination was performed with a sensitivity of 90% and a specificity of 72% by the energy underneath the squared modulus of the time-frequency distribution plots of the computed wavelet transforms.
Recommendations for Medical Informatics Training in The Netherlands
Authors: Hasman A. 
Published: March 2018

Abstract:In this contribution recommendations for education and training in Medical Informatics as they have been formulated end 1987 by the Subcommittee Medical Informatics of the Royal Netherlands Academy of Arts and Sciences are described. The current situation of education and training is presented and compared with the recommendations. It is concluded that not all recommendations have yet been followed up.
Twenty Years Medical Informatics Education at Heidelberg/Heilbronn: Evolution of a Specialized Curriculum for Medical Informatics
Authors: Leven F. J. , Haux R. 
Published: March 2018

Abstract:The medical informatics curriculum at University of Heidelberg/School of Technology Heilbronn started in 1972 as a specialized university curriculum. In this paper, we report on 20 years of experience and the evolution of this educational approach with respect to structure and content of the curriculum. We emphasize that this evolution parallels the development of medical informatics to a medical discipline in its own right, with distinct application domains and specific methodological approaches. Based on our experience and on recommendations from the national and international community, we describe and discuss the features of the curriculum.
ARMA – Filtering of Evoked Potentials
Authors: Heinze H.-J. , Künkel H. 
Published: March 2018

SummaryA method of evoked potential data processing alternative to the averaging method will be discussed. It is to extract evoked potentials only from two segments. The theoretical basis of this procedure is the so-called ARMA model which gives a high frequency resolution of a periodic signal mixed with noise in a relatively low signal-to-noise ratio. The method is tested by simulation studies. The applicability will be demonstrated by clinical examples.
A Stochastic Model for the Inheritance of the Cancer Proneness Phenotype
Authors: Tautu P. , Wagner G. 
Published: March 2018

SummaryA continuous parameter, stationary Gaussian process is introduced as a first approach to the probabilistic representation of the phenotype inheritance process. With some specific assumptions about the components of the covariance function, it may describe the temporal behaviour of the “cancer-proneness phenotype” (CPF) as a quantitative continuous trait. Upcrossing a fixed level (“threshold”) u and reaching level zero are the extremes of the Gaussian process considered; it is assumed that they might be interpreted as the transformation of CPF into a “neoplastic disease phenotype” or as the non-proneness to cancer, respectively.
The Kappa Coefficient and the Prevalence of a Diagnosis
Authors: Gjørup Thomas 
Published: March 2018

SummaryThe kappa coefficient is a widely used measure of agreement between observers’ independent recording of diagnoses. Kappa adjusts the overall agreement for expected chance agreement. The dependence of kappa on the prevalence . of a diagnosis has not previously been emphasized. This dependence means that kappa does not give a general statement of the reproducibility of a diagnosis. The result of a study of observer agreement should, therefore, not – as it has been done in several studies – be given by the kappa value alone. The kappa value should always be given together with the original results of the study.
A Knowledge-based System for Data Analysis and Interpretation
Authors: Chowdhury Shamsul , Wigertz Ove , Sundgren Bo 
Published: March 2018

Abstract:Traditionally, statistical packages are employed to derive or infer facts about a Universe of Discourse through data analysis and interpretation. It is analysis that serves to transform data into information. Statistical packages provide the users with relatively easy-to-use and powerful mechanics of data analysis, but up to now they do not provide much help with the design and strategies of the analysis. As such, there is a risk of misuse of these packages by statistically inexperienced users. We propose the use of knowledge-based interfaces to support this category of users in statistical evaluations. This paper discusses our experiences from the implementation of a knowledge-based system called MAXITAB. It provides guidance in the processes of data analysis and interpretation and has been programmed as an interface to the statistical package MINITAB.