bluuebunny/crossref_metadata_2025_split huggingface dataset:
Methodology of ECG Interpretation in the Padova Program
Authors: Degani R. , Bortolan G. 
Published: March 2018

AbstractThe main lines ofthe program designed for the interpretation of ECGs, developed in Padova by LADSEB-CNR with the cooperation of the Medical School of the University of Padova are described. In particular, the strategies used for (i) morphology recognition, (ii) measurement evaluation, and (iii) linguistic decision making are illustrated. The main aspect which discerns this program in comparison with other approaches to computerized electrocardiography is its ability of managing the imprecision in both the measurements and the medical knowledge through the use of fuzzy-set methodologies. So-called possibility distributions are used to represent ill-defined parameters as well as threshold limits for diagnostic criteria. In this way, smooth conclusions are derived when the evidence does not support a crisp decision. The influence of the CSE project on the evolution of the Padova program is illustrated.
Probabilistic Diagnosis Using a Reformulation of the INTERNIST-1/QMR Knowledge Base
Authors: Shwe M. A. , Heckerman D. E. , Henrion M. , Horvitz E. J. , Lehmann H. P. , Cooper G. F. , Middleton B. 
Published: March 2018

Abstract:In Part I of this two-part series, we report the design of a probabilistic reformulation of the Quick Medical Reference (QMR) diagnostic decision-support tool. We describe a two-level multiply connected belief-network representation of the QMR knowledge base of internal medicine. In the belief-network representation of the QMR knowledge base, we use probabilities derived from the QMR disease profiles, from QMR imports of findings, and from National Center for Health Statistics hospital-discharge statistics.We use a stochastic simulation algorithm for inference on the belief network. This algorithm computes estimates of the posterior marginal probabilities of diseases given a set of findings. In Part II of the series, we compare the performance of QMR to that of our probabilistic system on cases abstracted from continuing medical education materials from Scientific American Medicine. In addition, we analyze empirically several components of the probabilistic model and simulation algorithm.
Probabilistic Diagnosis Using a Reformulation of the INTERNIST-1/QMR Knowledge Base
Authors: Shwe A. M. , Heckerman E. D. , Henrion M. , Horvitz J. E. , Lehmann P. H. , Cooper F. G. , Middleton B. 
Published: March 2018

AbstractWe have developed a probabilistic reformulation of the Quick Medical Reference (QMR) system. In Part I of this two-part series, we described a two-level, multiply connected belief-network representation of the QMR knowledge base and a simulation algorithm to perform probabilistic inference on the reformulated knowledge base. In Part II of this series, we report on an evaluation of the probabilistic QMR, in which we compare the performance of QMR to that of our probabilistic system on cases abstracted from continuing medical education materials from Scientific American Medicine. In addition, we analyze empirically several components of the probabilistic model and simulation algorithm.
Expert System Design in Hematology Diagnosis
Authors: Diamond L. W. , Priolet G. , Sultan C. , Nguyen D. T. 
Published: March 2018

Abstract:A two-part study was designed to test the hypothesis that sufficient information is available from a modern hematology analyzer (the Coulter STKS) to reach a reliable intermediate conclusion which can be used as input to the next decision-making level in the design of a high-performance expert system for hematology diagnosis. In phase one, we analyzed the performance of three probabilistic systems (using Bayes’ rule) which interpret STKS data: a control system which took the traditional approach of classifying cases into specific diagnoses, and two test systems which were designed to reach only an intermediate conclusion but not a final diagnosis. One of the test systems classified cases into “textbook categories” of disease and the other utilized defined diagnostic patterns. The systems were tested with 150 cases. The pattern approach ranked the correct choice first in 141 of 150 cases (94%). In phase two, we abandoned Bayes’ rule, reformulated the pattern approach into a heuristic classification system, and tested its reliability on 820 cases. The algorithm of the reformulated system was able to classify all 820 cases into the same predominant pattern as a panel of three experienced laboratory hematologists.
A Genetic Algorithm to Improve a Neural Network to Predict a Patient’s Response to Warfarin
Authors: Narayanan M. N. , Lucas S. B. 
Published: March 2018

Abstract:The ability of neural networks to predict the international normalised ratio (INR) for patients treated with Warfarin was investigated. Neural networks were obtained by using all the predictor variables in the neural network, or by using a genetic algorithm to select an optimal subset of predictor variables in a neural network. The use of a genetic algorithm gave a marked and significant improvement in the prediction of the INR in two of the three cases investigated. The mean error in these cases, typically, reduced from 1.02 ± 0.29 to 0.28 ± 0.25 (paired t-test, t = −4.71, p <0.001, n = 30). The use of a genetic algorithm with Warfarin data offers a significant enhancement of the predictive ability of a neural network with Warfarin data, identifies significant predictor variables, reduces the size of the neural network and thus the speed at which the reduced network can be trained, and reduces the sensitivity of a network to over-training.
Philosophies for the Design and Development of Clinical Decision-Support Systems
Authors: Heathfield H. A. , Wyatt J. 
Published: March 2018

Abstract:Little significance is attached by medical informatics workers to the many practical issues which affect the development of clinical decision-support systems. We examine the current state of research in clinical decision-support, the characteristics and motivations of developers, and the perceptions of intended end-users. Factors which adversely affect the success of systems are highlighted and pointers to good practice discussed. We then propose a coherent approach to system development, consisting of requirements analysis, software design, implementation, testing, evaluation and maintenance.
Discrimination and Reproducibility of an Information Maximizing Multivariable Model
Authors: Conant R. C. , Tape Th. G. , Wigton R. S. , Heckerling P. S. 
Published: March 2018

Abstract:Predictor variables for multivariate rules are frequently selected by methods that maximize likelihood rather than information. We compared the discrimination and reproducibility of a prediction rule for pneumonia derived using extended dependency analysis (EDA), an information maximizing variable selection program, with that of a validated rule derived using logistic regression. Discrimination was measured by receiver-operating characteristic (ROC) analysis, and reproducibility by rederivation of the rule on 200 replicate samples of size 250 and 500, generated from a training cohort of 905 patients using Monte Carlo techniques.Four of the five predictor variables selected by EDA were identical to those selected by logistic regression. With each variable weighted by its conditional contribution to total information transmission, EDA discriminated pneumonia and nonpneumonia in the training cohort with an ROC area of 0.800 (vs 0.816 for logistic regression, p = 0.60), and in the validation cohort with an area of 0.822 (vs 0.821 for logistic regression, p = 0.98). EDA demonstrated reproducibility comparable to that of logistic regression according to most criteria for replicability. Replicate EDA models showed good discrimination in the training and testing cohorts, and met statistical criteria for validation (no significant difference in ROC areas at a one-tailed alpha level of 0.05) in 80.8% to 94.2% of cases.We conclude that extended dependency analysis selected the most important variables for predicting pneumonia, based on a validated logistic regression model. The information-theoretic model showed good discriminatory power, and demonstrated reproducibility according to clinically reasonable criteria. Information-theoretic variable selection by extended dependency analysis appears to be a reasonable basis for developing clinical prediction rules.
Integrated Clinical Decision Support Using an Object-Oriented Database Management System
Authors: Frost R. D. , Gillenson M. L. 
Published: March 2018

Abstract:Clinical decision support systems assist in diagnosis, alert to abnormal conditions, and manage patient data. Such systems tend to emphasize one of these features at the expense of the others and tend to be developed on an ad hoc basis. In this work, a technique is developed for creating an integrated clinical decision support system wholly within a general-purpose object-oriented database management system. The diagnostic and alerting requirements are accomplished with encapsulated methods and a novel use of the object-oriented database management class-hierarchy structure. The patient data management requirement is satisfied by the normal data management capabilities of the object-oriented DBMS.
Response of General Practitioners to Computer-Generated Critiques of Hypertension Therapy
Authors: van der Does E. , Man in ’t Veld A. J. , Musen M. A. , van Bemmel J. H. , van der Lei J. 
Published: March 2018

Abstract:We recently have shown that a computer system, known as HyperCritic, can successfully audit general practitioners’ treatment of hypertension by analyzing computer-based patient records. HyperCritic reviews the electronic medical records and offers unsolicited advice. To determine which unsolicited advice might be perceived as inappropriate, builders of programs such as HyperCritic need insight into providers’ responses to computer-generated critique of their patient care. Twenty medical charts, describing in total 243 visits of patients with hypertension, were audited by 8 human reviewers and by the critiquing-system HyperCritic. A panel of 14 general practitioners subsequently judged the relevance of those critiques on a five-point scale ranging from relevant critique to erroneous or harmful critique. The panel judged reviewers’ comments to be either relevant or somewhat relevant in 61 to 68% of cases, and either erroneous or possibly erroneous in 15 to 18%; the panel judged HyperCritic’s comments to be either relevant or somewhat relevant in 65% of cases, and either erroneous or possibly erroneous in 16%. Comparison of individual members of the panel showed large differences; for example, the portion of HyperCritic’s comments judged relevant ranged from 0 to 82%. We conclude that, from the perspective of general practitioners, critiques generated by the critiquing system HyperCritic are perceived equally beneficial as critiques generated by human reviewers. Different general practitioners, however, judge the critiques differently. Before auditing systems based on computer-based patient records that are acceptable to practitioners can be introduced, additional studies are needed to evaluate the reasons a physician may have for judging critiques to be irrelevant, and to evaluate the effect of critiques on physician behavior.
Work-Sampling: A Statistical Approach to Evaluation of the Effect of Computers on Work Patterns in Healthcare
Authors: Sittig D. F. 
Published: March 2018

Abstract:An increasing number of health-care institutions are in the process of implementing clinical computing systems. The need for an accurate assessment of the clinical, administrative, social, and financial effects of such systems has been recognized. Techniques have been developed to evaluate these effects on the work patterns of health-care workers including: time-motion analysis, subjective evaluations, review of departmental statistics, personal activity records, and work-sampling. This study reviews these techniques, discusses both positive and negative aspects, and presents a step-by-step description of work-sampling.
Distinguishing Individual Linkages of Personal Records from Family Linkages
Authors: Newcombe H. B. 
Published: March 2018

AbstractErrors occur in the automated linkage of medical and other records into personal histories, when household and family identifiers get wrongly treated in the same way as the strictly personal identifiers. This is because overwhelming evidence that two records refer to the same household or family, does not mean they necessarily represent the same person. Current practice in probabilistic record linkage fails to make this distinction, and combines indiscriminately the calculated odds from the mix of identifiers pertaining to all three sorts of entity. A tactic is described that avoids the resulting problem of mistaken personal identity. It does so by first converting composite odds from comparisons of household and family particulars, to a magnitude that contributes correctly to the overall evidence in favour of a strictly personal linkage.
Safety and Decision Support in Oncology
Authors: Harris A. L. , Das S. K. , Wyatt J. C. , Hammond P. 
Published: March 2018

Abstract:The management of patients with cancer involves the administration of complex treatment protocols with frequent monitoring of the effects of treatment on the malignant disease as well as on the general health of the patient. The number and wide variety of protocols used in treatment trials, and the amount of clinical data generated suggest the need for computer-based support. The toxicity of many of the treatments used and the severity of the disease itself underline the safety-critical nature of all decisions made by oncologists, the physicians and surgeons who treat cancer patients. This paper presents recent work on the analysis of safety issues arising from the design and implementation of a protoype decision-support system for oncologists. It illustrates the benefits of combining both informal and formal approaches to the analysis and representation of safety, firmly based on a thorough and detailed study of the domain in cooperation with oncologists, pharmacists and medical informaticians.
The Relative Accuracy of a Variety of Medical Diagnostic Programs
Authors: Todd B. S. , Stamper R. 
Published: March 2018

Abstract:Acute abdominal pain is one of the most widely studied applications of computer-aided diagnosis. The usual approach is to apply Bayes’ theorem with the assumption of conditional independence (“independence Bayes”). We compared various approaches to designing diagnostic programs for abdominal pain of suspected gynaecological origin. The methods range from statistical to knowledge-based. All programs were evaluated using a database of 1,270 cases collected retrospectively. Our results suggest that in this application no significant improvement in accuracy can be made by taking interactions into account, either by statistical or by knowledge-based means; independence Bayes is near-optimal. As far as accuracy is concerned, there appears to be little point in pursuing knowledge-based approaches. However, the “nearest neighbours” method using a new metric appears to be at least as accurate as independence Bayes. We argue that the nearest neighbours method is more suitable than independence Bayes for clinical use because of greater accountability.
A Compartmental Model for Simulation of IGF-I Kinetics and Metabolism
Authors: Sonksen P. H. , Jones R. H. , Boroujerdi M. A. 
Published: March 2018

Abstract:A compartmental model for the simulation of in-vivo insulin-like growth factor one (IGF-I) kinetics and metabolism is presented. The model is based on the concept that IGF binding proteins (IGFBPs) act as a reservoir for IGF-I in plasma, thereby restricting its access to the extravascular space. The model is divided into two subsystems; a binding model for IGF-I and IGFBP, and an IGF-I clearance model, which includes the binding of IGF-I to IGF-I receptors. The non-linear differential equations describing the model are based on the law of mass action. Given the steady state condition, the linearized form of the model, describing tracer kinetics of IGF-I and IGFBPs is developed. It is demonstrated that using the available data, it is possible to assign values to the model parameters, thereby allowing simulation of the model to obtain information not accessible by direct observation.
A Unified Approach to the Design of Clinical Reporting Systems
Authors: Salgado N. C. , Azevedo A. P. , Lopes L. , Raposo V. D. , Almeida I. , Galvão de Melo E. , Gouveia-Oliveira A. 
Published: March 2018

Abstract:Computer-based Clinical Reporting Systems (CRS) for diagnostic departments that use structured data entry have a number of functional and structural affinities suggesting that a common software architecture for CRS may be defined. Such an architecture should allow easy expandability and reusability of a CRS. We report the development methodology and the architecture of SISCOPE, a CRS originally designed for gastrointestinal endoscopy that is expandable and reusable. Its main components are a patient database, a knowledge base, a reports base, and screen and reporting engines. The knowledge base contains the description of the controlled vocabulary and all the information necessary to control the menu system, and is easily accessed and modified with a conventional text editor. The structure of the controlled vocabulary is formally presented as an entity-relationship diagram. The screen engine drives a dynamic user interface and the reporting engine automatically creates a medical report; both engines operate by following a set of rules and the information contained in the knowledge base. Clinical experience has shown this architecture to be highly flexible and to allow frequent modifications of both the vocabulary and the menu system. This structure provided increased collaboration among development teams, insulating the domain expert from the details of the database, and enabling him to modify the system as necessary and to test the changes immediately. The system has also been reused in several different domains.
An Information System for Epidemiology based on a Computer-Based Medical Record
Authors: Verdier C. , Flory A. 
Published: March 2018

Abstract:A new way is presented to build an information system addressed to problems in epidemiology. Based on our analysis of current and future requirements, a system is proposed which allows for collection, organization and distribution of data within a computer network. In this application, two broad communities of users – physicians and epidemiologists – can be identified, each with their own perspectives and goals. The different requirements of each community lead us to a client-service centered architecture which provides the functionality requirements of the two groups. The resulting physician workstation provides help for recording and querying medical information about patients and from a pharmacological database. All information is classified and coded in order to be retrieved for pharmaco-economic studies. The service center receives information from physician workstations and permits organizations that are in charge of statistical studies to work with “real” data recorded during patient encounters. This leads to a new approach in epidemiology. Studies can be carried out with a more efficient data acquisition. For modelling the information system, we use an object-oriented approach. We have observed that the object-oriented representation, particularly its concepts of generalization, aggregation and encapsulation, are very usable for our problem.
Patient Registration and Treatment Allocation in Multicenter Clinical Trials Using a FAX-OCR System
Authors: Kamakura T. , Sakamoto M. , Odaka T. , Nose Y. , Akazawa K. 
Published: March 2018

Abstract:This article describes the design and results of implementation of an automated patient registration and freatment allocation system (RETAS) used in multicenter clinical trials. RETAS was developed using a FAX-OCR system by which handwritten Japanese and English characters, as well as numericals and forms with check boxes, are sent from participating institutions by Fax, processed using an optical character reader, and then transmitted to a host computer at a statistical center. Based on the facsimile data, RETAS can automatically review eligibility, collect patient identification data and provide a randomized treatment allocation. RETAS permits uninterrupted, unattended operation at a statistical center, 24 hours a day, 7 days a week. Therefore, it drastically decreases the workload of personnel at the statistical center needed to support central telephone registration coverage. Consequently, staff members are free to focus on patient registration, treatment allocation, and follow-up of patients. The treatment allocation procedure in this system is based on Pocock and Simon’s minimization method combined with Zelen’s method for institution balancing. By this system it was possible to balance treatment numbers for each level of various prognostic factors over an entire trial and, at the same time, balance the allocation of treatments within an institution. The system currently supports the protocol of a clinical trial for Adjuvant Chemo-Endocrine Therapy for Breast Cancer in West Japan.
Myositis Netz
Authors: Zschüntzsch J. , Preusse C. , Ruck T. , Meuth S. G. , Müller-Felber W. , Stenzel W. , Schmidt J. ,   für das Myositis Netz
Published: March 2018

ZusammenfassungEntzündliche Muskelerkrankungen stellen eine wichtige Gruppe der seltenen neuromuskulären Erkrankungen dar. Die Diagnose der Myositiden hat einen besonderen Stellenwert, da sie im Gegensatz zu vielen anderen hereditären neuromuskulären Erkrankungen kausal behandelt werden können. Daher ist eine rasche, genaue Diagnosestellung wichtig, um Patienten helfen zu können, bevor irreversible Defizite entstehen. Um Patienten mit der Diagnosestellung einer Myositis und deren Angehörigen bessere Informationen über die Erkrankung zu ermöglichen, hat sich vor einigen Jahren innerhalb der Selbsthilfe der Deutschen Gesellschaft für Muskelkranke e. V. die Diagnosegruppe Myositis gebildet (www.dgm.org). Zum interdisziplinären Austausch von Ärzten und Wissenschaftlern wurde 2015 das Myositis Netz gegründet, welches eine Plattform für wissenschaftliche Kooperationen bietet (www.myositis-netz.de). Hauptziele des Myositis Netz sind es, die Therapie bei Myositis zu optimieren und standardisieren und die Wissenschaft in diesem Bereich zu fördern. In dem vorliegenden Beitrag soll das Myositis Netz mit seinen Aufgaben, Zielen und Teilnehmern vorgestellt werden. Darüber hinaus werden die wesentlichen Fakten zur Diagnostik und Therapie der Myositis kompakt und übersichtlich dargestellt.
Functional Characteristics of a Computerized Medical Record
Authors: Hammond W. E. , Stead W. W. , Straube M. J. , Jelovsek F. R. 
Published: March 2018

Research-based clinical information systems are presently being developed. This paper discusses some characteristics which such systems must have to be successful and affordable outside the research world. Problems of data entry, verification, and correction must be dealt with. Programs must be bug-free, and provisions must be made for data protection and integrity, for growth of record files, and for the ultimate purging of those files.Functional characteristics of a computerized medical record — TMR — developed at Duke University are presented, based on three health care facilities : the University Health Services Clinic with an active file of 33,000 patients; the Renal Dialysis Unit of the Durham Veterans Hospital with an active file of 300 patients; and the Department of Obstetrics and Gynecology with an active file of 7,000 patients. These functional characteristics include the rate of growth of files, the length of various components of the record, the type and length of program modules, and various system function response times.