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Relationships among performance scores of four diagnostic decision support systems.

OBJECTIVE: To examine the relationships among different performance scores for each of four diagnostic decision support systems (DDSSs). DESIGN: Intercorrelations among seven performance scores on a set of 105 cases for each of four DDSSs (DXplain, Iliad, Meditel, QMR) were computed. METHODS: The performance scores for each case reflected: 1) presence or absence of the case diagnosis in the DDSS knowledge base; 2) presence or absence of the correct diagnosis anywhere on the DDSS diagnosis list; 3) presence or absence of the correct diagnosis in the top ten diagnoses; 4) relevance of the DDSS diagnosis list; 5) comprehensiveness of the DDSS diagnosis list; 6) whether the DDSS suggested additional diagnoses to the experts' list; and 7) the length of the DDSS diagnosis list. RESULTS: For all DDSSs, the two Correct Diagnosis scores (top ten and total list) were significantly related: 1) to the presence of the correct diagnosis in the knowledge base; 2) to the Comprehensiveness score; and 3) to each other. There were significant differences among the four DDSSs on the magnitude and/or direction of the relationships between: 1) the two Correct Diagnosis scores; 2) the Relevance and Length scores; and 3) the Relevance and Additional Diagnoses scores. CONCLUSION: The production of a correct diagnosis for a given case is not related to the number of diagnoses suggested by the DDSS and, across different DDSSs, is not consistently related to other measures of performance. These data indicate that multiple measures are needed to fully describe the performance of a DDSS.

Algorithms↗

Towards improved knowledge sharing: assessment of the HL7 Reference Information Model to support medical logic module queries.

Because clinical databases vary in structure, access methods and vocabulary used to represent data, the Arden Syntax does not define a standard model for querying databases. Consequently, database queries are encoded in ad hoc ways and enclosed in "curly braces" in Medical Logic Modules (MLMs). However, the nonstandard representation of queries impairs sharing of MLMs, an impediment that has come to be known as the "curly braces problem." As a first step in solving this problem, we evaluated the proposed HL7 Reference Information Model (RIM) as a foundation for a standard query model for the Arden Syntax. Specifically, we analyzed the MLM knowledge base at the Columbia-Presbyterian Medical Center and compared the queries in these MLMs to the RIM. We studied 488 queries in 104 MLMs, identifying 674 total query data elements. Laboratory tests accounted for 45.8% of these elements, while demographic and ADT data accounted for 37.6%. Pharmacy orders accounted for 10.5%, medical problems for 4.3% and MLM output messages for 1.6%. We found that the RIM encompasses all but those data elements signifying MLM output (1.6% of the total). We conclude that the majority of queries in the CPMC knowledge base access a relatively small set of data elements and that the RIM encompasses these elements. We propose extensions of this analysis to continue construction of an Arden query model capable of solving the "curly braces problem."

Artificial Intelligence↗

Computer-aided diagnosis for lung cancer.

CAD methods may provide radiologists with tools to obtain more accurate diagnoses for lung cancer. Considerable effort has been devoted to developing CAD tools for CXR; however, these are limited by the fundamental constraints of the projective CXR modality. CT provides far more detailed information that can be exploited better by CAD systems. There has been very little work done in this area to date, although the basic technology has already been developed through the more extensive research in the computer vision areas supported by industry and the military. Initial prototype CT CAD systems have been described that are highly effective in detecting small pulmonary nodules and in predicting malignancy of nodules. CT is now achieving momentum in the study of lung cancer. It has taken time for this modality to gain acceptance because of several factors: higher radiation dose, higher cost, and the novelty of use in this application. It is important to note that the technology for CT scanners is still rapidly evolving. As the speed, resolution, and cost of CT scanners continue to improve, computer techniques for the measurement and analysis of nodules will also achieve corresponding improvements in accuracy and diagnostic utility. Future knowledge-based CT CAD systems will provide detailed analysis of the related conditions of the lungs, such as emphysema, and diagnostic analysis of nodules. The issue is not whether CAD will improve the performance and capabilities of the radiologist, but at what rate their development and the corresponding improvement will occur. Current prototype CAD systems may be considered as tools. As such they will improve the performance of the user/radiologist if they are well engineered and if the user understands their capabilities and limitations. These systems need to be improved by knowledge-based engineering, which is notoriously difficult to implement robustly and requires model refinement and optimization based on a large database of cases. Research should be directed at developing these methods rather than comparing prototype systems with current practices. Future performance should be expected to exceed that of today's grand masters.

Diagnosis, Computer-Assisted↗

Degradation model: a quantitative EIA instrument, acting as a decision support system (DSS) for environmental management.

Environmental assessment of alternative development plans, programs, and policies may bring conflict among decision-makers, particularly when some quantitative measures for decision-making are needed and where cumulative impacts are neglected. Environmental impact assessment (EIA) and environmental economics theories, despite their usefulness, are not capable of addressing those issues and problems alone. In recent years, the decision support system (DSS) has provided some solutions, but mathematical analysis of the system to show the internal structure of the problem is not always possible. To addres the above shortcomings and ongoing problems of decision-making in Iran, a degradation model (DM) was introduced as an instrument of EIA, to act as a DSS for managers. The model is a compromise between knowledge-based decision support systems, detailed models, digested information models, and the basic theorem of environmental economics. In the present study (1996-2000), the model was applied in three provinces of Iran, representing three of four biogeographical regions of Iran. The study area was divided into a set of grids (100 km(2)). The degradation coefficient ( H) was computed for all grids (1333), representing the degree of degradation in the grid. It is obvious that the higher the coefficient the more area is degraded and less prone to further development, and vice versa. In order to provide decision-makers with a set of quantitative measures to observe impacted areas (critical and noncritical) for resource allocation and further development, the degradation coefficients of all grids were classified into categories and criteria, using a fuzzy set theoretic approach. Accordingly, only 24% of study areas are prone to further development. The degradation model as a knowledge-based decision support system has its strengths and weaknesses, but it has solved managers' ongoing problems in Iran and it could be used elsewhere.

Conservation of Natural Resources↗

New signal processing techniques for the decomposition of EMG signals.

This paper relates to the use of knowledge-based signal processing techniques in the decomposition of EMG signals. The aim of the research is to automatically decompose EMG signals recorded at force levels up to 20 per cent maximum voluntary contraction (MVC) into their constituent motor unit action potentials (MUAPS), and to display the MUAP shapes and firing times for the clinician. This requires the classification of nonoverlapping MUAPs and superimposed waveforms formed from overlapping MUAPs in the signal. Nonoverlapping MUAPs are classified using a statistical pattern-recognition method. The decomposition of superimposed waveforms uses a combination of procedural and knowledge-based methods. The decomposition method was tested on real and simulated EMG data recorded at force levels up to 20 per cent MVC. The different EMG signals contained up to six motor units (MUs). The new decomposition program classifies the total number of MUAP firings in an EMG signal with an accuracy always greater than 95 per cent. The decomposition program takes about 15s to classify all nonoverlapping MUAPs in EMG signal of length 1.0s and, on average, an extra 9s to classify each superimposed waveform.

Action Potentials↗

Denatured proteins and early folding intermediates simulated in a reduced conformational space.

Conformations of globular proteins in the denatured state were studied using a high-resolution lattice model of proteins and Monte Carlo dynamics. The model assumes a united-atom and high-coordination lattice representation of the polypeptide conformational space. The force field of the model mimics the short-range protein-like conformational stiffness, hydrophobic interactions of the side chains and the main-chain hydrogen bonds. Two types of approximations for the short-range interactions were compared: simple statistical potentials and knowledge-based protein-specific potentials derived from the sequence-structure compatibility of short fragments of protein chains. Model proteins in the denatured state are relatively compact, although the majority of the sampled conformations are globally different from the native fold. At the same time short protein fragments are mostly native-like. Thus, the denatured state of the model proteins has several features of the molten globule state observed experimentally. Statistical potentials induce native-like conformational propensities in the denatured state, especially for the fragments located in the core of folded proteins. Knowledge-based protein-specific potentials increase only slightly the level of similarity to the native conformations, in spite of their qualitatively higher specificity in the native structures. For a few cases, where fairly accurate experimental data exist, the simulation results are in semiquantitative agreement with the physical picture revealed by the experiments. This shows that the model studied in this work could be used efficiently in computational studies of protein dynamics in the denatured state, and consequently for studies of protein folding pathways, i.e. not only for the modeling of folded structures, as it was shown in previous studies. The results of the present studies also provide a new insight into the explanation of the Levinthal's paradox.

Animals↗

Expert systems for the prediction of ovulation: comparison of an expert system shell (Expertech Xi Plus) with a program written in a traditional language (BASIC).

The use of an expert system shell (EXPERTECH Xi Plus) in the construction of an expert system for the diagnosis of infertility has been evaluated. A module was devised for predicting ovulation from the medical history alone. Two versions of this system were constructed, one using the expert system shell, and the other using QuickBASIC. The two systems have been compared with respect to: (1) ease of construction; (2) ease of knowledge base update; (3) help and explanation facilities; (4) diagnostic accuracy; (5) acceptability to patients and clinicians; (6) user-friendliness and ease of use; (7) use of memory space; and (8) run time. The responses of patients and clinicians were evaluated by questionnaires. The predictions made by the computer systems were compared to the conclusions reached by clinicians and to the "gold standard" of day 21 progesterone. The conclusions of this pilot study are: (1) the construction of this expert system was NOT facilitated by the use of this expert system shell; (2) update of the knowledge base was not facilitated either; (3) the expert system shell offered built-in help and explanation facilities, but as the system increased in complexity these became less useful; (4) after initial adjustment of decision thresholds the diagnostic accuracy of the system equalled that of the clinician; (5) the patient response to computer history-taking was very favorable but much less favorable to computer diagnosis; (6) the clinicians took a positive attitude to computer diagnosis; (7) the systems were easy to use; (8) the expert systems shell required much more memory space and had a much slower response time than the system written in BASIC.

Diagnosis, Computer-Assisted↗

[Utilization of expert systems in psychiatry].

Are expert systems liable to be used as consultants in psychiatry? Most expert systems deal with an over-restricted part of psychiatry and cannot be a real help in everyday care. Moreover, most of them are not actually validated (the comparison between the system's and the expert's conclusions in a few cases is not enough). Another problem is that they reflect the uncertainties of nosographic problems. Validation of such systems needs the careful checking of the logical structure of the underlying nosography, the fitness of the structure's knowledge base and the fitness of the inference engine. Moreover, the naïve use of the system by untrained clinicians is the best means of validation since it provides real life proof of the ability of expert systems to make diagnoses in unselected cases where the need for a common diagnostic reference is clear (for example, epidemiologic, psychopharmacological ornosographic research). Some of the best known expert systems in the field of psychiatry are reviewed and another expert system, Adinfer, is presented. Developed since 1982, Adinfer is a forward-tracking level O system (in its simplified version for micro-computers). The knowledge base is a translation of the DSM-III-R into production rules. The program has been included in several software packages and used in many clinical studies, both among psychiatrists and physicians. The program has been validated with 1,141 unselected cases, and with 47 physicians: an 83% agreement rate was found between the system's and the physician's diagnoses, taking into account that the clinicians were asked to give their conclusions according to their usual nosography.(ABSTRACT TRUNCATED AT 250 WORDS)

Artificial Intelligence↗

Object-oriented modeling and terminologies for drug contraindications.

There is no available standardized representation of contraindications that can be used in drug knowledge bases. In this paper, an object-oriented representation of contraindications is proposed that would allow computerized checking of drug prescription safety. It distinguishes four types of contraindications: pathological state, physiological state, findings of investigation procedures, and diagnostic or therapeutic procedures. The vocabulary usable for expressing the contraindications appropriate for automated prescription checking was also investigated. ICD10 (International Classification of Diseases, tenth revision), SNOMED III (Systematized Nomenclature of Medicine), ICPC (International Classification of Primary Care), and ATC (Anatomic Therapeutic and Chemical Classification) were studied as potential sources of standardized vocabulary. A system to support entering data on contraindications into a drug knowledge base, compatible with the proposed structure and using the identified vocabulary sources, is also presented.

Artificial Intelligence↗

Uncertainty assessment of VOC emissions from paint in The Netherlands using the NUSAP system.

We demonstrate an innovative approach to uncertainty assessment known as the NUSAP system, to assess qualitative and quantitative uncertainty for the case of emissions of volatile organic compounds (VOC) from paint in The Netherlands. Using expert elicitation, we identified key sources of error, critical assumptions, and bias in the monitoring process. We assessed pedigree and probabilistic uncertainty of all input quantities. We used four pedigree criteria to assess the strength of the knowledge base: proxy representation, empirical basis, methodological rigour and degree of validation. Using Monte Carlo analysis, we assessed sensitivity and propagation of uncertainty. Results for sensitivity and pedigree were combined in a 'NUSAP Diagnostic Diagram', which effectively highlighted the assumption for VOC percentage of imported paint as the weakest spot in the monitoring of VOC emissions. We conclude that NUSAP facilitates systematic scrutinization of method and underlying assumptions and structures creative thinking on sources of error and bias. It provides a means to prioritise uncertainties and focus research efforts on the potentially most problematic parameters and assumptions, at the same time identifying specific weaknesses in the knowledge base. With NUSAP, nuances of meaning about quantities can be conveyed concisely and clearly, to a degree that is not possible with statistic methods only.

Air Pollutants↗

Increasing returns and the new world of business.

Our understanding of how markets and businesses operate was passed down to us more than a century ago by English economist Alfred Marshall. It is based on the assumption of diminishing returns: products or companies that get ahead in a market eventually run into limitations so that a predictable equilibrium of prices and market shares is reached. The theory was valid for the bulk-processing, smokestack economy of Marshall's day. But in this century, Western economies have gone from processing resources to processing information, from the application of raw energy to the application of ideas. The mechanisms that determine economic behavior have also shifted--from diminishing returns to increasing returns. Increasing returns are the tendency for that which is ahead to get further ahead and for that which is losing advantage to lose further advantage. If a product gets ahead, increasing returns can magnify the advantage, and the product can go on to lock in the market. Mechanisms of increasing returns exist alongside those of diminishing returns in all industries. But, in general, diminishing returns hold sway in the traditional, resource-processing industries. Increasing returns reign in the newer, knowledge-based industries. Modern economies have split into two interrelated worlds of business corresponding to the two types of returns. The two worlds have different economics. They differ in behavior, style, and culture. They call for different management techniques, strategies, and codes of government regulation. The author illuminates those differences by explaining how increasing returns operate in high tech and in service industries. He also offers advice to managers in knowledge-based markets.

Commerce↗

The question of knowledge in district nursing.

This paper focuses on the development of the experiential knowledge base in district nursing with reference to changes in professional preparation for district nurses and to a research study conducted by the author during the 1970s. The process of conducting the research showed that an exclusive focus on activity fails to capture the range and depth of nursing care in the home. Schön's concept of professional artistry is employed as an interpretive framework to consider some of the study findings and with reference to more recent research studies the author concludes that while it has always been central to skilled nursing, professional artistry has remained hidden. The problems confronting academics and practitioners in articulating such knowledge are explored together with the possible consequences of continued failure to address this issue. These difficulties are discussed in the context of the current changes in the National Health Service with particular reference to the introduction of grade mix in community nursing. The paper concludes by arguing that a better understanding of the district nurse's knowledge base must be vigorously pursued.

Community Health Nursing↗

Programme budgeting and marginal analysis: application within programmes to assist purchasing in Greater Glasgow Health Board.

Recent NHS policy statements advocate the use of 'knowledge-based' purchasing. This paper describes an attempt to use an economic method to inform the purchasing process. The approach of programme budgeting and marginal analysis (PBMA) offers information on current service provision and provides a framework in which changes in a service can be evaluated and agreed within the context of a fixed budget. This has been applied to gynaecology services in Greater Glasgow Health Board and, following positive reaction to the results of this exercise, is now being extended into other areas. The process of carrying out the exercise is described. Additionally, limitations of the approach and the advantages of using PBMA in achieving knowledge-based purchasing are discussed.

Budgets↗

Nurses' reflections on problems associated with decision-making in critical care settings.

The present study investigated nurses' perceptions of the problems associated with their decision-making in critical care settings. This paper reports a survey of 230 Australian practising critical care nurses. In responses to a set of structured questions concerning various difficulties in making decisions, it was found that between 22 and 56% of nurses reported to be experiencing difficulties on a weekly or more frequent basis "due to knowledge base', "lack of time to make decisions', "lack of time to implement decisions', and "personal values conflicts with other staff'. Nearly one-third (30.3%) of the respondents indicated that they disagreed with other staff who were responsible for making decisions in their units on at least a weekly basis. The nurses were also invited to comment in writing on their concerns in a variety of areas. Major sources of nurse dissatisfaction included: treatment decisions for patients with poor prognoses; disharmony with medical staff concerning decision autonomy issues, especially with junior doctors; time constraints on nursing care: the demands of new intensive care technology upon the nurses' knowledge bases; and the need for in-service education to address this problem. The paper concludes with arguments for the use of in-depth interviews to further study these issues.

Adult↗

Integrating electronic information resources for NHS Glasgow staff at the point of need: a model of interlibrary collaboration and resource sharing.

The Glasgow NHS Libraries Consortium has harnessed the political imperative of collaboration and the capability of electronic information resources to address inequalities in access to the knowledge base across NHS Glasgow. They have negotiated consortium arrangements to an extensive range of electronic databases and journals which no single Glasgow NHS library could afford independently. A Project Officer was appointed to undertake the administration, technical work and promotion required to build a Web-based electronic library to deliver resources to all NHS Glasgow staff on an equitable basis. Close partnership with online content providers enabled the Project Officer to find solutions to problems caused by authentication systems and license restrictions. These efforts have culminated in the production of a fully integrated virtual library--the NHS Glasgow e-Library--delivering 11 major electronic databases, 440 full-text electronic journals, 48 electronic textbooks and over 5000 journal contents pages. The NHS Glasgow e-Library is without precedent within the NHS in terms of its wealth of resources, and it provides a model for Scotland-wide access to the knowledge base. The sustainability and transferability of the resource is dependent on a number of key areas-maintenance, user training, evaluation, IT infrastructure and ongoing collaboration and unification. Ongoing research will monitor how far the NHS Glasgow e-Library has strengthened the connection between research evidence and clinical practice.

Communication↗

Efficient methods for filtering and ranking fragments for the prediction of structurally variable regions in proteins.

The prediction of protein 3D structures close to insertions and deletions or, more generally, loop prediction, is still one of the major challenges in homology modeling projects. In this article, we developed ranking criteria and selection filters to improve knowledge-based loop predictions. These criteria were developed and optimized for a test data set containing 678 insertions and deletions. The examples are, in principle, predictable from the used loop database with an RMSD < 1 A and represent realistic modeling situations. Four noncorrelated criteria for the selection of fragments are evaluated. A fast prefilter compares the distance between the anchor groups in the template protein with the stems of the fragments. The RMSD of the anchor groups is used for fitting and ranking of the selected loop candidates. After fitting, repulsive close contacts of loop candidates with the template protein are used for filtering, and fragments with backbone torsion angles, which are unfavorable according to a knowledge-based potential, are eliminated. By the combined application of these filter criteria to the test set, it was possible to increase the percentage of predictions with a global RMSD < 1 A to over 50% among the first five ranks, with average global RMSD values for the first rank candidate that are between 1.3 and 2.2 A for different loop lengths. Compared to other examples described in the literature, our large numbers of test cases are not self-predictions, where loops are placed in a protein after a peptide loop has been cut out, but are attempts to predict structural changes that occur in evolution when a protein is affected by insertions and deletions.

Algorithms↗

Computers in critical care: opportunities and challenges.

Treating acutely ill patients in intensive care units (ICUs) requires assimilating large amounts of patient data. The computer can help process these data and display information in easy to understand formats. Also, knowledge-based systems can provide advice in diagnosis and treatment of common disorders in the ICU. For effective use of computers, systems must be integrated into the total hospital information system and computer data must logically become the primary medical record. Standards are being developed to aid in this process. Although computers have been used in the ICU for 25 years, most hospitals still use the paper medical record. Prototype systems such as the HELP, CARE, and PDMS systems are described. They are integrated ICU systems for computerizing most of the traditional functions in the ICU. Several commercial information management products are also described along with recently developed computerized drug and fluid delivery systems. Finally, prototype knowledge-based programs are presented that provide advice to the clinician on such topics as acid-base balance, hemodynamic monitoring, and shock management.

Artificial Intelligence↗

Sex differences in the effectiveness of elaborative strategy use: knowledge access comparisons.

Dual-task procedures-elaborative strategy use and finger-tapping-were used to examine both recall and mental effort demands of elaboration strategy use with equal numbers of boys and girls at grades two and three. Knowledge-base access was examined by comparing different item types in the associative learning list: masculine, feminine, and mixed. Results showed that boys and girls did not differ in their recall of arbitrarily paired items (e.g., mixed pairs). A Sex by Item Type (masculine vs feminine) interaction, however, revealed that for feminine pairs girls recalled more than boys, whereas for masculine pairs no sex difference was observed. Finger tapping interference scores indexed mental effort. Similar to the recall findings, results indicated that the elaboration of feminine pairs required less mental effort by girls in contrast to boys. Elaboration of masculine pairs was not associated with a sex difference. The results were discussed in terms of sex differences in knowledge-base access.

Child↗