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PubMed1992

Validation of the medical expert system PNEUMON-IA.

The present study validates the expert system PNEUMON-IA. The aim of PNEUMON-IA is assessing the etiology of community-acquired pneumonias from clinical, radiological, and laboratory data obtained at the onset of the disease. Validation was performed using data from medical records of 76 patients with proven clinical diagnosis of pneumonia. The etiological diagnoses provided by PNEUMON-IA were compared to those established by five specialists unrelated to the development of the expert system. For each etiological possibility, both PNEUMON-IA and the experts provided a causal possibility, expressed as a linguistic label (i.e., "almost impossible"). Linguistic labels were then converted to numeric values. In the majority of cases, an etiological diagnosis was unavailable to be used as a gold standard. To overcome this limitation, distances between arrays of etiological possibilities given by specialists and by PNEUMON-IA were considered as an agreement measure between diagnoses. Cluster analysis based on those distances was used to classify PNEUMON-IA among experts. Results showed the same differences between specialists and PNEUMON-IA as among the specialists themselves. The method used to validate PNEUMON-IA could prove useful to assess the performance of expert systems in fields where no gold standard is available.

Adolescent↗

PubMed1996

Development of an expert system for amino acid sequence identification.

An expert system for amino acid sequence identification has been developed. The algorithm uses heuristic rules developed by human experts in protein sequencing. The system is applied to the chromatographic data of phenylthiohydantoin-amino acids acquired from an automated sequencer. The peak intensities in the current cycle are compared with those in the previous cycle, while the calibration and succeeding cycles are used as ancillary identification criteria when necessary. The retention time for each chromatographic peak in each cycle is corrected by the corresponding peak in the calibration cycle at the same run. The main improvement of our system compared with the onboard software used by the Applied Biosystems 477A Protein/Peptide Sequencer is that each peak in each cycle is assigned an identification name according to the corrected retention time to be used for the comparison with different cycles. The system was developed from analyses of ribonuclease A and evaluated by runs of four other protein samples that were not used in rule development. This paper demonstrates that rules developed by human experts can be automatically applied to sequence assignment. The expert system performed more accurately than the onboard software of the protein sequencer, in that the misidentification rates for the expert system were around 7%, whereas those for the onboard software were between 13 and 21%.

Algorithms↗

PubMed1991

A performance evaluation of the expert system 'Jaundice' in comparison with that of three hepatologists.

The diagnostic performance of an Expert System (Jaundice) designed to discriminate between different causes of jaundice was evaluated in a test sample of 200 consecutive in-patients with serum bilirubin greater than or equal to 51 mumol/l. The average probability assigned to true diagnosis, the non-error rate and the overall accuracy were, respectively, 55%, 77% and 70%. The Expert System's discriminatory ability in probabilistic prediction, assessed by a method based on continuous functions of the diagnostic probabilities (Brier score) was good. We also compared the ability of our Expert System to that of three experienced hepatologists, who were required to give a diagnosis in 20 cases following the same protocol used by computer (i.e., by asking only clinical and laboratory items). Both the hepatologists and Jaundice achieved a correct diagnosis in 70% of 20 cases, but the Expert System asked a significantly higher average number of questions during each consultation. Analysis of the reasoning pathway made by an external referee showed a high agreement between the diagnostic strategies of the Expert System and the physicians. We conclude that Jaundice can be a useful tool to support a physician with insufficient clinical experience in this field to generate correct diagnostic hypotheses.

Diagnosis, Computer-Assisted↗

PubMed1989

The calcium-phosphorus metabolism expert system module: a program developed in the ALEX Smalltalk/V shell.

The object-oriented computing model of Smalltalk/V proved to be very well suited for the creation of a medical expert system on the diagnosis of calcium-phosphorus metabolism abnormalities. A major reason for this was that a disease could be viewed as a self-contained, active, entity. The expert system is implemented in ALEX, an expert system shell that is written in Smalltalk/V. The shell consists of classes and methods that can be modified, as needed, by the developer. The expert system is, at present, 140,000 bytes in size, and includes 43 diseases, arranged in 7 contexts. Sixty case reports were used to test the expert system. In 30 cases, there was complete agreement between clinician and expert system; in 12 cases, the expert system responded appropriately when presented with diseases that were not known to the system; and in 18 cases, the system gave plausible results.

Calcium↗

PubMedDate not supplied

Loading a nursing expert system from text: a case study.

A major bottleneck in the construction of expert systems has traditionally been the solicitation and formalization of expertise from the "human expert." As a means of reducing this bottleneck, the authors propose the use of "text" as a source of knowledge. Acquisition of knowledge from text has not been successful thus far, primarily because most text is not presented in a format (rules, frames, or logic) that can be directly used to load a knowledge base. The authors propose techniques to overcome these inherent problems. This article introduces a model for building an expert system that relies on "text" as the source of knowledge. The model is introduced via a case study involving the building of a nurse expert system designed to replicate the medical diagnostic activities of professional nurses.

Artificial Intelligence↗

PubMed1991

The value of an expert system in performing clinical drug trials.

An expert system has been designed to assist the cardiologist in determining whether patients can be included in clinical trials. This system contains knowledge on inclusion and exclusion criteria for six drug trials, and has been validated in 100 randomly selected patients. In 97 cases, the expert system and the cardiologist made an identical classification; in the remaining three cases, the patient was incorrectly classified by the physician. The system will also optimize the order in which questions are asked in order to minimize the time required to decide on inclusion or exclusion.

Angina, Unstable↗

PubMedDate not supplied

An expert system intervention for smoking cessation.

Intervention efficacy can be increased when the treatment is maximally matched to the needs of the client. One means of achieving such matching is through use of an expert system, a computer-based decision-making system designed to utilize client information to produce unique, matched information and interventions. An expert system can combine the individual matching possible in a clinic-based intervention and the low cost associated with a public health approach. This paper begins by discussing several alternative implementations of the expert system approach within the general context of communication theory. Second, the theoretical model and related empirical evidence which form the basis of the expert system is described briefly. Third, the details of a computer-driven, expert system intervention specifically developed for smoking cessation is described. Finally, empirical results from a study comparing the expert system intervention to three alternative interventions for smoking cessation are presented. In general, the expert system approach can provide a cost effective, viable, and efficacious means of intervening in a specific problem behavior area. Implications and potential areas of development are discussed.

Adult↗

PubMed2005

Screening of antibiotics resistance to Enterobacteriaceae, Pseudomonas aeruginosa, and Acinetobacter baumannii by an advanced expert system.

The VITEK2 advanced expert system (AES) gives information about the antibiotics-resistance mechanisms based on the biological validation derived from the VITEK2 susceptibility result. In this study, we investigated whether or not this system correctly categorized the beta-lactamase resistance mechanism data derived from the VITEK2 susceptibility result using the testing card, AST-N025, with Enterobacteriaceae, Pseudomonas aeruginosa, and Acinetobacter baumannii. We used 131 strains, and their phenotypes were determined according to the biological and genetic screening. The AES analysis result matched the phenotype testing in 120 (91.6%) of the 131 strains. Incorrect findings were found in six strains, including three strains of Serratia marcescens. The resistance mechanism could not be determined in five strains, including three strains of Providencia rettgeri. The analysis of those phenotypes agreed in 34 (97.1%) among 35 strains with extended spectrum beta-lactamase (ESBL), and in 27 (96.4%) among 28 strains with high-level cephalosporinase. The agreement ratio in the phenotype was very high as we expected. The incorrect and nondeterminable samples were strains with relatively high cephalosporinase that has variation of outer membrane protein. The AES was able to detect the phenotype for carbapenemase. The AES is a clinically useful system that allows taking prompt measures to treat patients because it can provide information about the resistance mechanism in less than half a day after starting the analysis.

Acinetobacter baumannii↗

PubMed1988

[Evaluation of ceftazidime treatment in septicemia expert systems].

The septicaemia expert-system (SES) consists of 18 departments of infectious diseases and microbiology in different French university hospitals. In this context, and compared with the totality of cases analyzed, ceftazidime was used by preference in worrying infections, i.e. often older patients, higher frequency of hospital-acquired infections and of multibacterial infections, greater number of pathogens regarded as difficult to eradicate. The results of ceftazidime treatment in these patients were not different from those obtained in the totality of cases.

Adolescent↗

PubMed1990

Overcoming deficiencies of the rule-based medical expert system.

One of the current deficiencies of the rule-based expert system is its static nature. As these systems are applied to medicine, this shortcoming becomes accentuated by: the rapid speed at which new knowledge is generated, the regional differences associated with the expression of many diseases, and the rate at which patient demographics and disease incidence change over time. This research presents a solution to the static nature of the rule-based expert system by proposing a hybrid system. This system consists of an expert system and a statistical analysis system linked to a patient database. The additional feature of a rule base manager which initiates automatic database analysis to refresh the statistical correlation of each rule ensures a dynamic, current, statistically accurate rule base. The philosophical differences between data and knowledge are also addressed as they apply to this type of hybrid system. The system is then used to generate four rule bases from different knowledge sources. These rule bases are then compared.

Artificial Intelligence↗

PubMed1985

OURCIN: a tool to build expert systems.

OURCIN is a tool to build expert systems, which was developed by a joint team from INRIA and SEMA. We emphasized developing on this system the ergonomic features which make Expert Systems a comfortable and interesting approach for knowledge engineering.

Computers↗

PubMed1988

Colonic lesion expert system. Performance evaluation.

A computer-based expert system for diagnosing colonic sections as normal, adenoma or adenocarcinoma is described, along with an evaluation of its performance. On the basis of its knowledge base, consisting of the values of diagnostic clues and their associated certainty factors for the possible diagnoses, the system will suggest the diagnosis for new cases presented to it. Using the data provided for 16 diagnostic clues, the system arrived at correct diagnoses for all cases of normal colon, for 49 of 50 cases of adenoma and for 48 of 49 cases of adenocarcinoma. Sample outputs from the expert system are presented and discussed, and the effects of possible alterations in the data base are considered.

Adenocarcinoma↗

PubMed1995

The importance of local data bases in medical expert systems: TICITL.

The database of our medical expert system, TICITL, contains the records of more than 15,000 gastroenterological patients. The data was collected over fifteen years (1977-1992) during which the patients were followed for at least three months to establish a final diagnosis. Using a new set of 230 gastroenterological cases, TICITL's first diagnosis was similar to the final diagnosis in 90% of the patients. When compared to foreign medical expert systems (M.E.S.), there is a considerable difference in diagnostic accuracy favorable to the local system. Another local program is also as accurate as TICITL. Consequently, we attribute these results to the database and strongly recommend employing real local patients whenever possible to implement M.E.S. in a new geographical area.

Databases, Factual↗

PubMed1992

[Detection of extended-spectrum beta-lactamases by the rapid ATB E technique. Value of the API V2.1.1 expert system].

Twenty-two extended-spectrum betalactamase-producing strains of enterobacteriaceae recovered in the authors' hospital were tested using the Rapid ATB E coupled with the API V2.1.1. expert system. The expert system detected 90.9% of ESBL-producing strains. Two strains producing a SHV2 and a CTX1, respectively, escaped detection by the expert system despite concomitant resistance to aminoglycosides.

4-Quinolones↗

PubMedDate not supplied

[An expert system to support diagnostic decision making by a neonatologist].

An "NATEX" expert system has been designed, which is intended to support a neonatologist's diagnostic decision making at the first stage of neonatal nursing. While designing the expert system, the authors used the shell "REPROCODE" wherein medical knowledge is presented as hierarchical semantic threshold network with shared attribute space. The designed system is realized on the basis of an IBM PC XT/AT, its operation requires only the processor 80286 and the operating system MS DOS 3.0 or higher. The "NATEX" expert system is employed to diagnose major syndromes of neonatal diseases. The knowledge base of the "NATEX" system has an account of 33 syndromes of neonatal diseases and, with various forms of severities borne in mind, the total number of diagnosed conditions in a baby is 63. In terms of content, it covers all major syndromes assessing the vital systems of the neonatal body and their occurring processes. The total number of symptoms which are necessary and sufficient for making a diagnostic decision as realization of either syndromes is 700.

Diagnosis, Computer-Assisted↗

PubMed1990

Towards validation of expert systems as medical decision aids.

Expert system evaluation is an important step in knowledge engineering development and is clearly not a simple process. The aim of this paper is to introduce methodological aspects of medical knowledge base validation. We distinguish two components of the evaluation: verification and validation. In the first part, the difficulties of evaluation are analysed, problems with some techniques used in the evaluation process are discussed. In the second part, our experiment gives guidelines to present these aspects and underline what and when to evaluate.

Decision Making, Computer-Assisted↗

PubMed1993

[An expert system for the staging and therapy of carcinoma of the bladder].

Expert systems are application tools based on logic and containing a wide knowledge in a specific field; their aim is the simulation of an expert's behavior in reasoning and making decisions inherent a small cultural domain. Applications in medicine and radiology are numerous and constantly increasing. The possibility of their use in the application of diagnostic and staging protocols seems particularly interesting. The development and commercial availability of expert systems programming tools (called shells) make it certainly easier to develop consultations systems, even to non-experienced users. The purpose of this research is the definition and description of the stages encountered during the development of an expert system for diagnosis, staging and treatment of bladder cancer using self-developed shell, designed for radiological use, called Experto. The steps of knowledge collection, definition of diagnostic and therapeutic protocols and system development are described. The consultation system assessed the correct TNM stage of the 27 examined cases.

Decision Trees↗

PubMed1989

Clinical expert systems versus linear models: do we really have to choose?

This article deals with decision subsystems at the level of the organism. In recent years there has been debate as to whether linear models or clinical expert systems make clinical decisions more effectively. Previous articles in this journal have favored linear models. This article argues the opposite case. We show that expert systems are not necessarily more expensive or less accurate than linear models and that, in theory at least, they can perform many tasks that are beyond the scope of linear models. Indeed, while a linear model may serve as a subsystem of a human or computer expert system, an expert system cannot be seen as a subsystem of a linear model. We conclude that clinical expert systems and linear models are not interchangeable and users should not be forced to choose between them.

Artificial Intelligence↗