bluuebunny/crossref_metadata_2025_split huggingface dataset:
How to Assess Prognostic Models for Survival Data: A Case Study in Oncology
Authors: Schumacher M. , Graf E. , Gerds T. 
Published: March 2018

Summary

Objectives:
A lack of generally applicable tools for the assessment of predictions for survival data has to be recognized. Prediction error curves based on the Brier score that have been suggested as a sensible approach are illustrated by means of a case study.

Methods:
The concept of predictions made in terms of conditional survival probabilities given the patient’s covariates is introduced. Such predictions are derived from various statistical models for survival data including artificial neural networks. The idea of how the prediction error of a prognostic classification scheme can be followed over time is illustrated with the data of two studies on the prognosis of node positive breast cancer patients, one of them serving as an independent test data set.

Results and Conclusions:
The Brier score as a function of time is shown to be a valuable tool for assessing the predictive performance of prognostic classification schemes for survival data incorporating censored observations. Comparison with the prediction based on the pooled Kaplan Meier estimator yields a benchmark value for any classification scheme incorporating patient’s covariate measurements. The problem of an overoptimistic assessment of prediction error caused by data-driven modelling as it is, for example, done with artificial neural nets can be circumvented by an assessment in an independent test data set.
Postmarketing Surveillance Based on Electronic Patient Records: The IPCI Project
Authors: van der Lei J. , Mosseveld B. M. Th. , van Wijk M. A. M. , van der Linden P. D. , Sturkenboom M. C. J. M. , van Bemmel J. H. , Vlug A. E. 
Published: March 2018

AbstractResearchers claim that data in electronic patient records can be used for a variety of purposes including individual patient care, management, and resource planning for scientific research. Our objective in the project Integrated Primary Care Information (IPCI) was to assess whether the electronic patient records of Dutch general practitioners contain sufficient data to perform studies in the area of postmarketing surveillance studies. We determined the data requirements for postmarketing surveil-lance studies, implemented additional software in the electronic patient records of the general practitioner, developed an organization to monitor the use of data, and performed validation studies to test the quality of the data. Analysis of the data requirements showed that additional software had to be installed to collect data that is not recorded in routine practice. To avoid having to obtain informed consent from each enrolled patient, we developed IPCI as a semianonymous system: both patients and participating general practitioners are anonymous for the researchers. Under specific circumstances, the researcher can contact indirectly (through a trusted third party) the physician that made the data available. Only the treating general practitioner is able to decode the identity of his patients. A Board of Supervisors predominantly consisting of participating general practitioners monitors the use of data. Validation studies show the data can be used for postmarketing surveillance. With additional software to collect data not normally recorded in routine practice, data from electronic patient record of general practitioners can be used for postmarketing surveillance.
Finding Ethical Principles and Practical Guidelines for the Controlled Flow of Patient Data
Authors: Draper R. , Hamilton I. , Rigby M. 
Published: March 2018

AbstractThe application of computing to health care, and particularly to electronic patient records, offers major benefits but raises issues of confidentiality and of potential misuse. Sound access control mechanisms are therefore important, but most models focus upon informed consent by the data subject. This raises challenges in mental health care, and for other vulnerable patients including those comatose, and the severely ill and temporarily distressed. Published algorithms which are used to control record access within a controlled environment therefore have value, as a means of ensuring an open and informed, yet ethically sound, solution. The paper describes the background and issues, and gives an example of such an algorithm.
The Multifarious Function of Medical Records: Ethical Issues
Authors: Spyropoulos B. , Papagounos G. 
Published: March 2018

AbstractMedical records comprise history data, physical examination, biosignals, data acquired through in vitro diagnostic tests, images, therapeutic data, and administrative data. Beyond the use of records for therapy, they are also used in research, teaching, the allocation of resources, and for the construction of the patient’s personal history. These functions give rise to a number of important ethical issues. The most important ethical issues are the patient’s autonomy in decisions pertaining to proposed therapeutic interventions, the confidentiality of the information contained in the records, the reliability of the information for research, and questions related to healthcare policy and the distribution of healthcare resources.
Automated Semantic Indexing of Imaging Reports to Support Retrieval of Medical Images in the Multimedia Electronic Medical Record
Authors: Antipov I. , Hersh W. , Smith C. A. , Mailhot M. , Lowe H. J. 
Published: March 2018

AbstractThis paper describes preliminary work evaluating automated semantic indexing of radiology imaging reports to represent images stored in the Image Engine multimedia medical record system at the University of Pittsburgh Medical Center. The authors used the SAPHIRE indexing system to automatically identify important biomedical concepts within radiology reports and represent these concepts with terms from the 1998 edition of the U.S. National Library of Medicine’s Unified Medical Language System (UMLS) Metathesaurus. This automated UMLS indexing was then compared with manual UMLS indexing of the same reports. Human indexing identified appropriate UMLS Metathesaurus descriptors for 81% of the important biomedical concepts contained in the report set. SAPHIRE automatically identified UMLS Metathesaurus descriptors for 64% of the important biomedical concepts contained in the report set. The overall conclusions of this pilot study were that the UMLS metathesaurus provided adequate coverage of the majority of the important concepts contained within the radiology report test set and that SAPHIRE could automatically identify and translate almost two thirds of these concepts into appropriate UMLS descriptors. Further work is required to improve both the recall and precision of this automated concept extraction process.
The Need for Open Geographical Information Systems in Medicine
Authors: Friebe J. , Grawunder M. , Wellmann I. , Appelrath H.-J. 
Published: March 2018

AbstractThis paper presents a promising approach of using component-oriented geographical information systems (GIS) to facilitate improved medical and ecological applications. The integration of administrative geographical and medical data (map overlay) allows sophisticated and advanced analysis. This can serve as a basis to detect undiscovered relationships. We hope to increase the usage of geographical information by the creation of a general framework. This approach is mainly supported by two advances in recent years. Geographical data (e.g. administrative areas) is up-to-date, consistent and covers Germany completely. In addition, enormous technological improvements in the area of high-bandwidth networks and component-based software development have been made. These advances allowed to define our general framework for the integration of GIS functions into existing and already accepted applications.
Medical Informatics and Problem-based Learning
Authors: Hasman A. , Boshuizen H. P. A. 
Published: March 2018

AbstractProblem-based learning (PBL) is an educational method that can be considered as an alternative to the traditional, discipline-based, approach to teaching. In this paper the characteristics of both approaches are discussed and compared. Some background knowledge concerning the principles that determine the success of instructional methods is presented. Finally, it is discussed how medical informatics can be taught in a PBL environment.
A Model and Application for Estimating Completeness of Registration
Authors: Stronegger W.-J. , Wernecke K.-D. , Berghold A. 
Published: March 2018

AbstractCompleteness of population-based registration systems is recognized to be an important aspect of the quality of information in registries which has to be examined. In this paper a model is presented which was used to estimate completeness of reporting of Down syndrome data notified to the Styrian Malformation registry between 1985-92. The model introduced is based on the two-source capture-recapture method allowing for time-varying parameters. For estimation of the parameters a discrete-time filtering algorithm was developed. For the used data set, an estimate of completeness derived from this model was in good agreement with an independent estimator based on demographic data and maternal age-specific Down syndrome risks whereas the usual two-source capture-recapture method gave a higher estimate.
Determining First Admissions in a Hospital Discharge File via Record Linkage
Authors: Langley J. D. , Alsop J. C. 
Published: March 2018

Abstract:The aim of this study was to identify first admissions in a public hospital discharge file with the greatest possible accuracy. Computerised data linkage was used to link injury events. This involved the use of “internal” data linkage (unduplication) which, in data linkage terms, is equivalent to matching two identical files. Admission status indicators obtained from deterministic and probabilistic linkages were compared with those obtained from a manual review. Small absolute reductions in error were obtained using a probabilistic linkage over a deterministic linkage. However, these reflected large relative reductions in error. A validity check confirmed initial results and discounted against possible bias due to the subjective nature of the probabilistic linking procedure.
Automatic Record Hash Coding and Linkage for Epidemiological Follow-up Data Confidentiality
Authors: Bouzelat H. , Allaert F. A. , Benhamiche A. M. , Faivre J. , Dusserre L. , Quantin C. 
Published: March 2018

AbstractA protocol is proposed to allow linkage of anonymous medical information within the framework of epidemiological follow-up studies. The protocol is composed of two steps; the first concerns the irreversible transformation of identification data, using a one-way hash function which is used after spelling processing. To avoid dictionary attacks, two large random files of keys, called pads, are introduced. The second step consists in the linkage of files rendered anonymous. The weight given to each linkage field is estimated by a mixture model, the likelihood of which being maximized with the Expectation and Maximization (EM) algorithm. The performance of this method has been assessed by comparing record linkage, based on exclusive use of the automatic procedure, with a manual linkage, obtained by the Burgundy Registry of Digestive Cancers. The result of the linkage of a file of 2,847 cancers with a file of 388,614 hospitalization stays in the Dijon university hospital showed a sensitivity of 97% and a specificity of 93%.
Evolution of Artificial Neural Network Architecture: Prediction of Depression after Mania
Authors: Pendleton N. , Lucas C. P. , Lucas S. B. , Horan M. A. , Jefferson M. F. 
Published: March 2018

AbstractArtificial neural networks (ANNs) are compared to standard statistical methods for outcome prediction in biomedical problems. A general method for using genetic algorithms to "evolve" ANN architecture (EANN) is presented. Accuracy of logistic regression, a fully interconnected ANN, and an EANN for predicting depression after mania are examined. All methods showed very good agreement (training set accuracy, chi-square all p <0.01). However, significant differences were found for stability (test set accuracy); logistic regression being the most unstable and EANN being significantly more stable than a fully interconnected ANN (McNemar p <0.01). We conclude that the EANN method enhances ANN stability. This approach may have particular relevance for biomedical prediction problems, such as predicting depression after mania.
On the Heuristic Nature of Medical Decision-Support Systems
Authors: Aliferis C. F. , Miller R. A. 
Published: March 2018

Abstract:In the realm of medical decision-support systems, the term “heuristic systems” is often considered to be synonymous with “medical artificial intelligence systems” or with “systems employing informal model(s) of problem solving”. Such a view may be inaccurate and possibly impede the conceptual development of future systems. This article examines the nature of heuristics and the levels at which heuristic solutions are introduced during system design and implementation. The authors discuss why heuristics are ubiquitous in all medical decision-support systems operating at non-trivial domains, and propose a unifying definition of heuristics that encompasses formal and ad hoc systems. System developers should be aware of the heuristic nature of all problem solving done in complex real world domains, and characterize their own use of heuristics in describing system development and implementation.
Sharing of Worldwide Spread Knowledge Using Hypermedia Facilities & Fast Communication Protocols (Mosaic and World Wide Web): The Example of ExPASy
Authors: Appel R. D. , Golaz O. , Pasquali Ch. , Sanchez J.-C. , Bairoch A. , Hochstrasser D. F. 
Published: March 2018

Abstract:The sharing of knowledge worldwide using hypermedia facilities and fast communication protocols (i.e., Mosaic and World Wide Web) provides a growth capacity with tremendous versatility and efficacy. The example of ExPASy, a molecular biology server developed at the University Hospital of Geneva, is striking. ExPASy provides hypermedia facilities to browse through several up-to-date biological and medical databases around the world and to link information from protein maps to genome information and diseases. Its extensive access is open through World Wide Web. Its concept could be extended to patient data including texts, laboratory data, relevant literature findings, sounds, images and movies. A new hypermedia culture is spreading very rapidly where the international fast transmission of documents is the central element. It is part of the emerging new “information society”.
The ICD Family of Classifications
Authors: Gersenovic M. 
Published: March 2018

Abstract:The history from the Sixth to the Ninth Revisions of the ICD is described. The 10th revision is presented as the 21st Century classification. The preparation of the ICD-10 included a long process with two expert committee meetings. A classification of diseases can be defined as a system of categories to which morbid entities are assigned according to established criteria. The pupose of the ICD is to permit the systematic analysis, interpretation and comparison of mortality and morbidity data collected in different countries or areas and at different times. In practice, the ICD has become the international standard diagnostic classification for all general epidemiological and many health management purposes. It was felt that the main ICD (the three- and four-character classification), covered by three volumes of ICD-10, could not incorporate all this additional information and remain accessible, and relevant to its traditional users, so the idea arose of a “family” of disease and health-related classifications, including volumes published separately form the main ICD, to be used as required. A statistical classification of diseases must be confined to a limited number of mutually exclusive categories, able to encompass the whole range of morbid condition, and must have well defined place in the list of categories. Consequently, throughout the classification, there will be residual categories for other and miscellaneous conditions that cannot be allocated to the more specific categories. As few conditions as possible should be classified to residual categories. Consequently, throughout the classification, there will be residual categories for other and miscellaneous conditions that cannot be allocated to the more specific categories. As few conditions as possible should be classified to residual categories. A broad description of ICD-10 itself, including information on applications, conventions, and general principles for use are described.
Distribution-Free Confidence Bounds for ROC Curves
Authors: Hilgers R. A. 
Published: March 2018

AbstractROC curves are widely used for the evaluation of diagnostic tests to decide between “healthy” and “diseased” individuals when the measurements are on a continuous scale. These curves are graphical displays of the interdependence between specificity and sensitivity of the test varying with the cut-off point chosen for the decision. Up to now only point estimators derived from the empirical distribution functions are used which may be misleading if they are based on rather small samples. In this paper we propose reasonable confidence bounds for ROC curves and a corresponding point estimator. Our bounds are strongly related to two-sided distribution-free tolerance regions because they are can, structed from minimum and maximum coverages which at a given value.t can be guaranteed with a confidence (2π* - 1). The interpretation of the bounds is that if a cut-off-point is chosen on the basis of the ROC curve then with a nominal confidence of at least (2π* -1)2 the real sensitivity and specificity will be within a rectangle.
Surveillance of Occupational Risks Using Job-Exposure Matrices
Authors: Mouaddib A. , Huy-Simon C. , Robaux P. , Martin J. M. 
Published: March 2018

AbstractThis article deals with the problem of surveillance of occupational risks of workers. Computer-assisted elaboration of the job history (JH) for each worker was achieved by means of a job-exposure matrix (JEM) for each company. The final aim of the project is to find correlations between the exposure data of JHs and the health data of corresponding medical records.As a first experiment, some JEMs were computed using rectangular arrays even though it was realized that this simple structure was not really adequate. Later on, the structure of the computerized JEM included the following questions: (1) what types of information are involved; (2) how can the job-exposure correspondence be represented in the computer; (3) what characteristics of a company should be used for the elaboration of a JEM; (4) who is to construct each JEM, and how? This article shows the inadequacy of some occupational names for evoking the appropriate risks, a drawback which can be surmounted if the company organization is included in the JEM. Based on our analysis, several specifications useful for JEM computerization have been suggested.
Dilemmas at a Primary Health Care Center: a baseline study for Computer-Supported Cooperative Health Care Work
Authors: Timpka T. , Nyce J. M. 
Published: March 2018

Abstract:For the development of computer-supported cooperative health care work this study investigated, based upon activity theory, daily dilemmas encountered by the members of interprofessional primary health care work groups. The entire staff at four Swedish primary health care centers were surveyed, 199 personal interviews being conducted by the Critical Incident Technique. Medical dilemmas were mainly reported by general practitioners and nurses, organizational dilemmas by laboratory staff, nurses’ aides, and secretaries, and dilemmas in the patient-provider relation by nurses, nurses’ aides, and secretaries. Organizational and communication dilemmas reported by nurses, nurses’ aides, and secretaries often had their cause outside the control of the individual professional. These dilemmas were often “caused” by other group members (general practitioners or nurses), e.g., by not keeping appointment times or by not sharing information with patients. The implication for computer-supported cooperative health care work is that computer support should be planned on two levels. Collective work activity as a whole should benefit from individual clinical decision support for general practitioners and nurses. However, since most patient communication and organizational problems occurred at group level, group process support is required in these areas.
Towards an Essential Data Set: Applicability in the Domain of Maternal Health Services
Authors: Singh A. K. , Boström K. , Chowdhury S. , Trell E. , Wigertz O. , Kjessler B. , Moidu K. 
Published: March 2018

Abstract:There is a need for consensus on the quantity of data that must be available in a computer-based information system of a health care organization. In this paper we take up the issue of defining the data content of an information system and introduce the concept of Essential Data Sets with an explicit methodology which was applied to define a data set for the Maternal Health Services program. A key step in the method was a recognized technique used in systems development process called data modelling, in this case infological modelling, by an interdisciplinary group. A preliminary set of 86 data elements was identified and it provided the foundation for development of an application software for discussion and a real-world testing framework. The acceptability of the data set was tested in a laboratory perspective by retrospective data entry from records of 94 pregnant women registered at a maternal health care center in Sweden. Data from a total of 1,318 prenatal visits, an outcome visit, and a postnatal visit for each woman was entered into a computer using the software, with no loss of information. Thus, in a short-term perspective the acceptability of the data set was demonstrated. The software has since been implemented for pilot prospective studies at sites in India and Sweden. The use of a common data protocol is an essential foundation for patient outcome research, especially as the trend of health care management has changed from a “process of care” orientation to an “outcome of care” orientation.
Validation of the AI/RHEUM Knowledge Base with Data from Consecutive Rheumatological Outpatients
Authors: Moens H. J. 
Published: March 2018

Abstract:The diagnostic accuracy of AI/RHEUM, an experimental expert system for support in the diagnosis of rheumatic diseases, was assessed using a collection of data in a cohort of 1,570 consecutive outpatients of a Dutch rheumatological clinic. Computer diagnoses based on these data and diagnostic predictions made by rheumatologists were compared with reference diagnoses that had been obtained by consensus of rheumatologists after 6-12 months follow-up.Performance of the tested version of the AI/RHEUM knowledge base is presented by various methods. Sensitivity varied between 29% and 100% for different rheumatological diseases. Average sensitivity and specificity for all 26 diagnoses present in the knowledge base were 67% and 98%, respectively. Performance according to the level of confidence indicated that 78% of the “definite”, 65% of the “probable”, and 33% of the “possible” conclusions made by AI/RHEUM were in agreement with the reference diagnoses. These results approximated the predictions made by rheumatologists after a single, initial examination. The system was less accurate than it had appeared in previous evaluation studies with complex clinical cases. The AI/RHEUM knowledge base needed refining to diagnose early rheumatic complaints. This study further illustrates the need for objective and informative parameters for expressing accuracy of diagnostic support systems.