bluuebunny/crossref_metadata_2025_split huggingface dataset:
Computer-Aided Diagnosis in Jaundice: Comparison of Knowledge-based and Probabilistic Approaches
Authors: Molino F. , Furia D. , Bar F. , Battista S. , Cappello N. , Molino G. 
Published: March 2018

AbstractThe study reported in this paper is aimed at evaluating the effectiveness of a knowledge-based expert system (ICTERUS) in diagnosing jaundiced patients, compared with a statistical system based on probabilistic concepts (TRIAL). The performances of both systems have been evaluated using the same set of data in the same number of patients. Both systems are spin-off products of the European project Euricterus, an EC-COMACBME Project designed to document the occurrence and diagnostic value of clinical findings in the clinical presentation of jaundice in Europe, and have been developed as decision-making tools for the identification of the cause of jaundice based only on clinical information and routine investigations. Two groups of jaundiced patients were studied, including 500 (retrospective sample) and 100 (prospective sample) subjects, respectively. All patients were independently submitted to both decision-support tools. The input of both systems was the data set agreed within the Euricterus Project. The performances of both systems were evaluated with respect to the reference diagnoses provided by experts on the basis of the full clinical documentation. Results indicate that both systems are clinically reliable, although the diagnostic prediction provided by the knowledge-based approach is slightly better.
Abductive Machine Learning for Modeling and Predicting the Educational Score in School Health Surveys
Authors: Mangoud A. M. , Abdel-Aal R. E. 
Published: March 2018

Abstract:The use of modern abductive machine learning techniques is described for modeling and predicting outcome parameters in terms of input parameters in medical survey data. The AIM® (Abductory Induction Mechanism) abductive network machine-learning tool is used to model the educational score in a health survey of 2,720 Albanian primary school children. Data included the child’s age, gender, vision, nourishment, parasite infection, family size, parents’ education, and educational score. Models synthesized by training on just 100 cases predict the educational score output for the remaining 2,620 cases with 100% accuracy. Simple models represented as analytical functions highlight global relationships and trends in the survey population. Models generated are quite robust, with no change in the basic model structure for a 10-fold increase in the size of the training set. Compared to other statistical and neural network approaches, AIM provides faster and highly automated model synthesis, requiring little or no user intervention.
Toward an Evaluation of an Integrated Clinical Imaging System: Identifying Clinical Benefits
Authors: Lundsgaarde H. P. , Kaplan B. 
Published: March 2018

Abstract:Integrated clinical imaging systems can provide the foundation for future computer-based patient record systems as recommended by the Institute of Medicine. However, documenting the benefits of such systems is difficult. This paper reports an evaluation of a clinical imaging system that is integrated with an on-line electronic patient record. The evaluation used interviews and observations to identify what physicians thought were the benefits of this system. Reported benefits may be classified into patient care benefits, educational benefits, and productivity and cost-reduction benefits. Physicians said that the imaging system provided patient care benefits by: improving clinical communication and decision making, making care more patient-based, reducing the number of procedures and patient risks, and improving record keeping. Educational benefits they reported included: improving communication, providing broad “real” experience, and improving supervision. These benefits may be reflected in increased productivity and cost reduction by increasing time savings, reducing clerical work, improving morale, and reducing the costs of care. The approach described in this study was valuable in identifying potential benefits of a clinical information system. The findings point the way to realization of benefits for other systems, and, ultimately, for computer-based patient records.
Decision Support Systems in Health Care
Authors: Walus Y. E. , Hanmer L. , Ittmann H. W. 
Published: March 2018

Abstract:This paper delineates the application of decision support systems in the healthcare arena. An overview of decision support systems in the healthcare environment in the last three to five years, mostly in the USA and the UK is provided. Some reference is made to work in South Africa. Although this report endeavours to emphasise the decision support system side, some operations research issues are also addressed. This paper is divided into several sections: decision support systems definition, techniques used, the use of operations research in specific areas of healthcare, information systems, assessment of decision support systems, in-house development, decision support in South Africa and future of decision support systems.
The Use of Knowledge-based Systems in Medicine in Developing Countries: A Luxury or a Necessity?
Authors: du Plessis J. P. , Tolmie C. J. 
Published: March 2018

Abstract:Knowledge-based systems (KBSs) in medicine have received much attention over the past two decades, mainly because of the potential benefits that can be gained from using them. They may facilitate in increasing productivity in a medical environment, support the making of diagnoses and other types of medical decisions, assist in the training of medical professionals, and can even handle some routine tasks in a medical environment. However, some critical problems in this field have also been identified. For example, research indicated that some problems can be solved partially, but not completely, with existing artificial intelligence techniques. Another problem is that many of the existing medical information systems do not support the integration of KBSs in a natural way. Furthermore, the routine use of a medical KBS is complicated by legal issues. These and other problems contribute to what we experience today: a large proportion of the medical KB applications that are developed is never actually used in practice. This justifies questions such as: Should developing countries, having limited infrastructure and research resources, invest in medical KBSs research and development, or should this field be regarded as a luxury that only belongs to developed countries?, and: Can developing countries really benefit from the use of these systems? These questions are discussed in this paper. We highlight the main problems surrounding the development and use of medical KBSs. With the focus on developing countries we discuss potential benefits that could be obtained by investing in these systems and we offer guidelines for focusing research and development of medical KBSs.
Data-Screening and Retrieval of Medical Data by the System WAREL
Authors: Dorda W. G. 
Published: March 2018

AbstractThe paper presented here deals with the computer system WAREL, a system for analyzing medical patient data. It is a patientoriented medical data-screening system which automatically points out medical risk factors. Referring to all patients, it is a retrieval system for selecting groups of patients from the clinical data base; the explorative statistical analysis concerning medical data of these selected groups can give an essential impulse to clinical research. The most important components of the system such as the relational data base and the system for defining and activating logical conditions are discussed. These conditions (IF -THEN rules) are the basis of both the patient oriented data-screening and the retrieval of patient groups. They may refer to data in formatted or in natural language form; furthermore conditions of the course of illness can also be formulated. Thus, the data-screeni ng system may also indicate risk situations due to the course of an illness.
Information Content of Diagnostic Tests in the Medical Literature
Authors: Heckerling P. S. 
Published: March 2018

AbstractDiagnostic tests provide information about the presence or absence of disease. However, even after application of diagnostic tests, significant uncertainty about the state of the patient often remains. This uncertainty can be quantified through the use of information theory. The “information” contained in diagnostic tests published in the medical literature of the years 1982 through 1986 was evaluated using Shannon information functions. Information content, averaged over all prior probabilities of disease, ranged from 0.002 bits to 0.720 bits of information; the tests therefore provided from 0.3% to 100% of the information needed for diagnostic certainty. Median average information was 0.395 bits, corresponding to only 55% of the information required for diagnostic certainty. Reclassifying test results into multiple mutually exclusive outcome categories allowed extraction of a median of 14% and a maximum of 109% more average information than that obtained using a dichotomous positive/negative classification. We conclude that the “information” provided by many of the tests published in the medical literature is insufficient to overcome diagnostic uncertainty. Information theory can quantify the uncertainty associated with diagnostic testing and suggest strategies for reducing this uncertainty.
Proposed Methodology for Knowledge Acquisition: A Study on Congenital Heart Disease Diagnosis
Authors: Leãot F. B. , Rocha F. A. 
Published: March 2018

Abstract
“Knowledge and human power are synonymous, since the ignorance of the cause frustrates the effect:…“
Francis Bacon1
This paper proposes a methodology for knowledge acquisition (KA) from multiple experts, in an attempt to elicit the heuristic rules followed by the physician in diagnosing twelve frequently occurring congenital heart diseases (CHD). Twenty-two pediatric cardiologists and twenty-three general cardiologists were interviewed with this technique; 274 interviews were conducted, 169 with the 22 experts, 105 with the 23 non-experts. A graph formalism was employed to represent their reasoning model, leading to the construction of a “mean reasoning model” for each diagnosis, separately for experts and non-experts. The results indicate that experts, compared to non-experts, tend to build knowledge representation models (KRM) that are smaller and less complex. Qualitative differences in information utilization between the two groups were also observed. Entropy analysis suggests a greater objectivity and cohesion of the experts’ model.
BRAINDEX: An Interactive, Knowledge-Based System Supporting Brain Death Diagnosis
Authors: Schwarz G. , Grims R. , Rumpl E. , Rom G. , Pfurtscheller G. , Haase V. 
Published: March 2018

AbstractBRAINDEX (Brain-Death Expert System) is an interactive, knowledge-based expert system offering support to physicians in decision making concerning brain death. The physician is given the possibility of communicating in almost natural language and, therefore, in terms with which he is familiar. This updated version of the system is implemented on an IBM-PC/AT with the expert system shell PC-PLUS and consists of about 430 rules. The determination of brain death is realized with backward chaining and for the optional coma-scaling a forward-chaining mechanism is used.
Methodology of ECG Interpretation in the Louvain Program
Authors: Brohet C. R. , Derwael C. , Robert A. , Fesler R. 
Published: March 2018

AbstractThe Louvain program performs the analysis and interpretation of the vectorcardiogram (VCG) to increase the clinical utility of ECG analysis. Among its original features, there are (1) a high-resolution vector-loop display for visual analysis, (2) quantitative analysis of the spatial VCG using age-sex stratified limits, (3) separate software for adult and pediatric series and (4) complementary deterministic and statistical methods of diagnostic classification. Using objective, ECG-independent evidence as a reference standard, the Louvain program has shown satisfactory levels of diagnostic accuracy in most basic categories. However, its usefulness is especially marked in “borderline” or “complex” situations, where the 12-lead ECG cannot provide a clear answer. It corresponds to the concept of “computer-assisted ECG interpretation” as opposed to “computer ECG analysis”.
A Medical Text Analysis System for German - Syntax Analysis
Authors: Pietrzyk P. M. 
Published: March 2018

Abstract:Much information about patients is stored in free text. Hence, the computerized processing of medical language data has been a well-known goal of medical informatics resulting in different paradigms. In Gottingen, a Medical Text Analysis System for German (abbr. MediTAS) has been under development for some time, trying to combine and to extend these paradigms. This article concentrates on the automated syntax analysis of German medical utterances. The investigated text material consists of 8,790 distinct utterances extracted from the summary sections of about 18,400 cytopathological findings reports. The parsing is based upon a new approach called Left-Associative Grammar (LAG) developed by Hausser. By extending considerably the LAG approach, most of the grammatical constructions occurring in the text material could be covered.
Validation, Clinical Trial, and Evaluation of a Radiology Expert System
Authors: Kahn C. E. 
Published: March 2018

Abstract:The PHOENIX Radiology Consultant is a rule-based expert system which assists physicians in planning radiological work-up strategies. This article describes the methods used to create and validate the system’s knowledge base. The feasibility and acceptability of PHOENIX were tested for two years in a clinical trial. During this period, the system was used 1,421 times, an average of 13.7 times per week, primarily by medical students and nonradiologist physicians. Much of the system’s use occurred at night and on weekends, when the radiology department was not fully staffed. Several physicians were enlisted to further evaluate the utility of the system. The results of their evaluation indicate that an expert system that helps physicians select diagnostic-imaging studies can serve as a useful and informative component of a radiology information system, and is particularly useful for medical students and physicians in training.
Data Modeling for Immunological and Clinical Data of Leukemia and Myasthenia Patients
Authors: Haux R. , Müller’ C. A. , Gerneth F. 
Published: March 2018

Abstract:In this study it was investigated whether and to what extent semantic data models and their methods for data modeling are useful for adequate representation and integration of immunological and clinical data. To that end the special research program in leukemia research and immunogenetics (SFB 120) of the University of Tübingen was taken as an example. Based on the semantic data model RIWT we propose the design of a database system, report on its realization, and discuss this approach. Using a semantic data model, the quality of data increased considerably. This means, for instance, that the integration of the molecular-biological knowledge allows a better control of the person-related results. Hence, the decisions based of these data may have greater validity and the treatment on leukemia patients can be improved. Furthermore, the elucidation of immune mechanisms concerning auto-immune diseases could be improved.
Eurosentinel: Development of an International Sentinel Network of General Practitioners
Authors: Leurquin P. , van Casteren V. 
Published: March 2018

Abstract:The Eurosentinel project was a European concerted action. It started in June 1988 and ended in June 1991. Its purpose was to coordinate activities in the field of sentinel practices with GPs and the ultimate goal was to establish a real European network of sentinel practices. This paper deals with the purposes of the project, the studies carried out in the frame of the project, and an evaluation of three years Eurosentinel.
Possibilities of Software Phantoms for Quality Control of KBS in Nuclear Medicine
Authors: Kotzke K. , Pretschner D.-P. 
Published: March 2018

Abstract:The assessment of the results of a “knowledge-based system” (KBS) for quality control is a basic requirement for clinical application: Large numbers of test studies are necessary in order to cover as widely as possible the spectrum of cases to be analyzed by the KBS. The use of original patient data as test data is one possibility, but real data are provided unevenly. This is due to the set of characteristics which are relevant to the analysis. Data are available in a limited quantity only. This implies a remaining set of unvalidated cases which are not represented in the data pool. The software phantom is an approach towards systematically guided validation. It permits the generation of test data adjusted to the demands of the validation.
A New Method to Assess the Difficulty of a Medical Diagnosis: Application to Electrocardiographic Interpretation
Authors: Willems J. L. , Girard P. , Morlet D. , Arnaud P. 
Published: March 2018

Abstract:A new method to assess the relative difficulty of a medical diagnosis and the efficacy of a diagnostic procedure is described. The cases within a population are classified by N independent interpreters, i. e., medical experts or computer programs. The percentages of correctly diagnosed cases by N (unanimity), N-1, N-2, ..., zero interpreters, respectively, are calculated. These Nl + 1 percentages are presented in a histogram. A cumulative plot is derived from the “unanimity” value. The ratio “unanimity value”/“zero value” is proposed as an index of diagnostic performance. An application to the CSE database is presented which is composed of 1,220 electrocardiographic tracings interpreted by 13 cardiologists and 15 computer programs. The cumulative plots, the performance index and Log (index) values, established for eight different diagnostic statements, clearly show the relative degree of diagnostic difficulty for each of them and the particular efficacy of each approach, i. e., electrocardiography versus vectorcardiography, and computerized versus human interpretation.
Developmental Toxicity Risk Assessment: A Rough Sets Approach
Authors: Jelovsek F. R. , Razzaghi M. , Hashemi R. R. 
Published: March 2018

Abstract:A rough-sets approach was applied to a data set consisting of animal study results and other compound characteristics to generate local and global (certain/possible) sets of rules for prediction of developmental toxicity in human subjects. A modified version of the rough-sets approach is proposed to allow the construction of an approximate set of rules to use for prediction in a manner similar to that of discriminant analysis. The modified rough-sets approach is superior in predictability to the original form of rough-sets methodology. In comparison to discriminant analysis, modified rough sets (approximate rules) appear to be better in overall classification, sensitivity, positive and negative predictive values. The findings were supported by applying the modified rough sets and discriminant analysis on a test data set generated from the original data set by using a resampling plan.
Advanced Patient Records: Some Ethical and Legal Considerations Touching Medical Information Space
Authors: Kluge E.-H. W. 
Published: March 2018

Abstract:The application of advanced computer-based information technology to patient records presents an opportunity for expanding the informational resource base that is available to health-care providers at all levels. Consequently, it has the potential for fundamentally restructuring the ethics of the physician/patient relationship and the ethos of contemporary health-care delivery. At the same time, the technology raises several important ethical problems. This paper explores some of these implications. It suggests that the fundamental ethical issue at stake in these developments is the status of the electronic record which functions as the analog of the health-care consumer in health-care decision making. Matters such as control and patient dignity are implicated. Other important ethical issues requiring solution include data ownership, data liability, informed consent to use and retrieval, security and access. The paper suggests that the ethical problems that arise cannot be solved in piecemeal fashion and on a purely national basis. They should be addressed in a coordinated international fashion and receive appropriate legal expression in the relevant countries and be incorporated into appropriate codes of ethics.
Automatic Knowledge Acquisition from MEDLINE
Authors: Barnett G. O. , Cimino J. J. 
Published: March 2018

Abstract:Construction of medical knowledge bases for use in expert systems is an arduous task. We propose a procedure for obtaining medical knowledge via automated analysis of citations found in the National Library of Medicine’s Medline
® database. In this method, simple pattern of keywords and subheading co-occurrences are detected in the keyword descriptor portion of the citations. Each pattern corresponds to a fact, expressed as a semantic relationship between medical concepts. We have constructed a set of 504 pattern-matching rules and applied it to a set of 673 Medline
® citations to produce 2,795 such facts. The results are presented of an analysis of the syntactic and semantic features of these facts to understand the kinds of knowledge than can be obtained through our method and speculate on the potential uses and pitfalls for knowledge of this type.
Constructing a Minimal Diagnostic Decision Tree
Authors: McGorry P. D. , Wallace C. S. , Low L. H. , Copolov D. L. , Singh B. S. , McKenzie D. P. 
Published: March 2018

Abstract:Classification trees and discriminant function analysis were employed in order to ascertain whether a small number of diagnostic decision rules could be extracted from a large inventory of items. Several models, involving up to 17 symptoms, that led to a broad psychiatric diagnosis were then tested on a small validation sample of 53 patients. All methods, with the exception of CART used without any pruning, generated identical trees involving four items. Almost 90% of the validation sample was able to be correctly classified by all methods although poor classification performance was noted in the case of one particular diagnosis, Schizoaffective Psychosis. In contrast, stepwise linear discriminant analysis originally selected 17 items, although three out of the first four items selected were identical to those chosen by the tree-building methods. Although more research is required, there are indications that the latter methods may be usefully employed in constructing parsimonious decision trees.
A Temporal Query System for Protocol-Directed Decision Support
Authors: Das A. K. , Musen M. A. 
Published: March 2018

Abstract:Chronus is a query system that supports temporal extensions to the Structured Query Language (SQL) for relational databases. Although the relational data model can store time-stamped data and can permit simple temporal-comparison operations, it does not provide either a closed or a sufficient algebra for manipulating temporal data. In this paper, we outline an algebra that maintains a consistent relational representation of temporal data and that allows the type of temporal queries needed for protocol-directed decision support. We also discuss how Chronus can translate between our temporal algebra and the relational algebra used for SQL queries. We have applied our system to the task of screening patients for clinical trials. Our results demonstrate that Chronus can express sufficiently all required temporal queries, and that the search time of such queries is similar to that of standard SQL.