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Results for “Software Validation”

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At least 55 records · Page 3Linked to original sources

PubMed1991

[Bacterio-expert: an integrated system for assisting in the validation of antibiotic sensitivity tests. Retrospective application in 4053 Staphylococcus].

Bacterio-expert is a simple expert system for assisting in the validation of antibiotic sensitivity testing. This system is incorporated in a data acquisition and editing program for bacteriologic test (Bacterio program written in Turbo-Pascal for personal computer users by the same authors). The principles of this system are explained and results with 4,053 antibiotic sensitivity tests on Staphylococcus aureus isolates are reported. Approximately 10% of tests required corrections.

Anti-Bacterial Agents↗

PubMedDate not supplied

Validation of a detailed computer model for the electric fields in the brain.

A computer model has been designed for the calculation of the electrical fields in the head, based on the finite difference method. This method has not previously been applied for head modelling. The model was validated by using three concentric spheres and comparing it with an analytic model. Three levels of accuracy were tested. The forward solutions show that the finite difference algorithm works correctly and, by selecting the size of the volume elements properly, accurate results are obtained. The model will be applied to accurate and realistic geometries of the human head obtained from magnetic resonance images.

Brain↗

PubMed1988

A performance evaluation of the expert system ANEMIA.

This paper reports the results of an evaluation study of the current level of performance given by ANEMIA, a knowledge-based consultation system addressing the clinical problem of managing anemic patients. ANEMIA was developed on a mainframe using the AI programming scheme EXPERT and then translated into a version running on a personal computer. At present the system is able to provide assistance in the diagnosis and management of 65 disease entities. After extensive local testing of accuracy, completeness, and consistency of the knowledge base included into ANEMIA, we designed a study to evaluate whether the system is able to appropriately mirror also the reasoning of well-known hematologists other than those who provided the knowledge. We were also interested in testing whether there were conflicting opinions among hematologists. Thus, we designed a validation study in which ANEMIA's performance could be compared with that of six hematologists and the interexpert consensus evaluated. ANEMIA's overall performance was judged acceptable in 87% (26/30) of the cases, while expert evaluators agreed with their colleagues in 90% (27/30) of them. A low interexpert consensus was found: considering the ratings given by different hematologists to the same ANEMIA performance, complete agreement occurred only 47% of the time.

Adult↗

PubMed1994

An expert system for the analysis and interpretation of evoked potentials based on fuzzy classification: application to brainstem auditory evoked potentials.

EPEXS is an expert system for evoked potential analysis and interpretation (a medical examination performed in clinical neurophysiology laboratories), working from available clinical records and numerical data extracted from evoked potential traces. EPEXS integrates two formalisms of knowledge representation: rules and structured objects. The rules represent the elementary concepts (shallow knowledge) and include a model of possibility based on the Dubois and Prade default reasoning and possibility theory. The structured objects (prototypes) are organized as hierarchical taxonomies (underlying knowledge). These allow the description of both the objects and their relationships. The heuristics used to interpret knowledge are based on two hypotheses: the unicity of the pathological process leading to several given symptoms and the progression from the general to the specific, leading to the adoption or rejection of a class of diagnoses. This avoids the problem of the differential diagnosis. These sources of knowledge are used in a dynamical way that could be described as a four-step process: acquisition of clinical data in order to define the nosological frame of the pathology, production of hypotheses about the nature and topography of lesions, interpretation of data in accordance with these hypotheses, and finally evaluation of their likelihood. The validation shows that EPEXS topographic diagnoses were correct in 100% of cases and 92% of it nosologic diagnoses were correct, and no pathological record was interpreted as normal. When examined on a given pathology basis EPEXS was not significantly different from human experts as regards to performance, specificity, and sensitivity.

Computer Simulation↗

PubMed1995

A computer program linking physiologically based pharmacokinetic model with cancer risk assessment for breast-fed infants.

The risk assessment process predicts the chances of adverse health effects that the toxicant possibly can do to the target organism under expected conditions of exposure. Regulators chose among several mathematical approaches to estimate the risk, but in each case it is necessary to link the dosemetrics of the toxicant with its predicted health effect. In this paper, a computer program is described that allowed us to link a physiologically based pharmacokinetic (PBPK) model for tetrachloroethylene (PCE) in the lactating mother with the estimate of extra cancer risk for breast-fed infants, according to the U.S. Environmental Protection Agency (EPA) methodology. When inhaled by a lactating woman, PCE may partition into breast milk and may be transferred to the breast-fed infant. We have developed and validated experimentally a PBPK model for lactational transfer of PCE in rats, including a quantitative description of a milk compartment and the nursing pup. Subsequently, the model has been scaled to describe human physiology, and was validated with literature data for human cases of PCE exposure. Finally, we linked the dosage predictions of the PBPK model with equations used by EPA to estimate the cancer risk from PCE. The model predictions are in good agreement with both the measured values and those reported in the literature for exposure to PCE. This comparison confirms the usefulness of PBPK modeling in risk assessments.

Air Pollutants↗

PubMed1989

A computer-based interview system for patients with back pain. A validation study.

A microcomputer-based system has been designed to interview patients with a view to investigating and establishing common syndromes of back and leg pain. In a randomized crossover validation study, 50 consecutive outpatients were interviewed by the computer and had a conventional clerking by a doctor. The conventional clerking made minor errors in 3.75% of questions answered and major errors in 0.90%. The computer made minor errors in 6.75% of questions and major errors in 5.45%. The majority of the computer errors were due to inadequate question design. These have been corrected, and it is anticipated that the computer will now have an overall rate of 94% correct answers and be sufficiently accurate to pursue the aim of clinical syndrome identification.

Back Pain↗

PubMed1995

Computer analysis of monophasic action potentials: manual validation and clinically pertinent applications.

Monophasic action potential (MAP) recordings are increasingly being used in a variety of clinical and experimental situations but their manual measurement is cumbersome, especially when hundreds or thousands of beats must be analyzed to monitor the exact time course of action potential duration (APD) changes following heart rate alterations, during surveillance of APD alternans, or during the onset and stabilization of Class III drug effects. To facilitate this task we developed a computer program that automates programmed electrical stimulation, digitizes at 1-kHz sampling frequency MAP recordings up to 8 channels simultaneously, analyzes all APDs at repolarization levels from 10%-90% in 10% decrements (APD10-90), and automatically outputs the analyzed numerical data into spreadsheets for graphical display or statistical analysis. To validate the computer algorithm, two independent observers manually analyzed 585 concurrent MAP recordings at a paper speed of 100 mm/s. Cycle length measurements by the computer were precise to 0.4 +/- 0.5 ms as compared to the computer determined paced cycle length. Computer measurements of APD20, 50, and 90 differed from manual measurements by 2.0 +/- 8.8 ms, 0.7 +/- 7.9 ms, and 0.2 +/- 8.5 ms, respectively, for observer 1; and by 12.2 +/- 8.3 ms, 5.8 +/- 7.5 ms, and 1.4 +/- 10.1 ms, respectively, for observer 2. Inter-observer variability (IOV) was 10.3 +/- 11.1 (APD20), 5.1 +/- 9.0 ms (APD50), and 1.2 +/- 7.8 ms (APD90), which was similar to computer/observer-2 differences and significantly greater (0.001) than computer/observer-1 differences. This indicates that the computer analysis was at least as precise as manual measurements when compared to IOV, and more precise when comparing computer/observer-1 differences to IOV. While providing equal or greater precision, computer-aided analysis of 100 MAP signals took approximately 1 minute while manual analysis of the same data set took between 2.5 and 4 hours. The pacing and analysis software was subsequently applied to experiments that mimic clinically pertinent examples of MAP recordings: (1) automatic generation, analysis, and graphical display of electrical restitution curves at multiple ventricular sites simultaneously; (2) evaluation of myocardial pharmacokinetics by monitoring the progression of Class III antiarrhythmic drug effects by continuous MAP recordings, and displaying differences in drug action between multiple sites; (3) depiction of the adaptation time course of APD to abrupt changes in paced cycle length; and (4) quantitative analysis of APD alternans during myocardial ischemia. The results show that our computerized algorithm greatly facilitates the generation of cardiac electrophysiological, and clinically important, data.

Action Potentials↗

PubMedDate not supplied

Machine learning for an expert system to predict preterm birth risk.

OBJECTIVE: Develop a prototype expert system for preterm birth risk assessment of pregnant women. Normal gestation involves a term of 40 weeks, but because 8-12% of the newborns in the United States are delivered prior to 37 weeks' gestation, problems associated with prematurity continue to plague individuals, families, and the health care system. DESIGN: A knowledge-base development methodology used machine learning, statistical analysis, and validation techniques to analyze three large datasets (18,890 subjects and 214 variables). The dependent (i.e., decision) variable studied was weeks of gestation at delivery, with dichotomous coding of preterm delivery (prior to 37 weeks) and full-term delivery (37+ weeks). RESULTS: Machine learning with a program named Learning from Examples using Rough Sets (LERS) induced 520 usable rules that were entered into a prototype expert system. The prototype expert system was 53-88% accurate in predicting preterm delivery for 9,419 patients. CONCLUSION: The prototype expert system was more accurate than traditional manual techniques in predicting preterm birth.

Adult↗

PubMed1991

Validation, clinical trial, and evaluation of a radiology expert system.

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.

Algorithms↗

PubMed1994

Medical data and knowledge management by integrated medical workstations: summary and recommendations.

The health care professional workstation will function as an interface between the user and the patient data as well as an interface pertinent medical knowledge. Appropriate knowledge focus will require the workstation to recognize the concepts and structure of patient data, and understand the scope and access methods of knowledge sources. Issues are organized around five major themes: (i) structure, (ii) reliability and validation, (iii) views, (iv) location, and (v) ethical and legal. Conventional database representations can effectively address data structure and format variations that will inevitably persist in local data stores. The reliability of data and the validation of knowledge are critical issues that may determine the ultimate utility of clinical workstations. Alternative views of patient information and knowledge sources represent the true power of an intelligent data portal, represented by a well-designed clinical workstation. Both data and knowledge are optimally represented in decentralized information networks, although the confidentiality and ownership of this information must be respected. Evolutionary progress toward consistent representations of knowledge and patient data will be facilitated by the establishment of self-documentation standards for the developers of data encoding systems and knowledge sources, perhaps extended from the preliminary model afforded by the Unified Medical Language System (UMLS).

Computer Security↗

PubMed1994

Validation of the medical expert system RENOIR.

RENOIR is an expert system developed to assist the diagnosis of 37 diseases of connective tissue and inflammatory arthropathies. Precise diagnosis of rheumatic diseases implies great uncertainty and there is no gold standard with which to compare the expert system output. To overcome this problem a set of clinical cases was submitted to RENOIR and its diagnoses were compared with those of clinicians. Medical records of 81 patients with rheumatic diseases were interpreted by RENOIR and by 12 clinicians at three different expertise levels in rheumatology. Distances between the likelihoods of the 37 considered diseases provided by clinicians and RENOIR were computed as a disagreement measure. Mahalanobis distance was used to correct the collinearity between the possibilities of each pair of diseases. Using the resulting matrices of distances between experts, cluster analyses were carried out to classify RENOIR among human experts. Greater differences between RENOIR and clinicians than among clinicians themselves were not found.

Cluster Analysis↗

PubMed1994

Automatic detection of wave boundaries in multilead ECG signals: validation with the CSE database.

This paper presents an algorithm for automatically locating the waveform boundaries (the onsets and ends of P, QRS, and T waves) in multilead ECG signals (the 12 standard leads and the orthogonal XYZ leads). Given these locations, features of clinical importance (such as the RR interval, the PQ interval, the QRS duration, the ST segment, and the QT interval) may be measured readily. First, a multilead QRS detector locates each beat, using a differentiated and low-pass filtered ECG signal as input. Next, the waveform boundaries are located in each lead. The leads in which the detected electrical activity is of longest duration are used for the final determination of the waveform boundaries. The performance of our algorithm has been evaluated using the CSE multilead measurement database. In comparison with other algorithms tested by the CSE, our algorithm achieves better agreement with manual measurements of the T-wave end and of interval values, while its measurements of other waveform boundaries are within the range of the algorithm and manual measurements obtained by the CSE.

Algorithms↗

PubMed1991

Analysis of brain and cerebrospinal fluid volumes with MR imaging. Part I. Methods, reliability, and validation.

A computerized system was developed to process standard spin-echo magnetic resonance (MR) imaging data for estimation of brain parenchyma and cerebrospinal fluid (CSF) volumes. In phantom experiments, the estimated volumes corresponded closely to the true volumes (r = .998), with a mean error less than 1.0 cm3 (for phantom volumes ranging from 5 to 35 cm3), with excellent intra- and interobserver reliability. In a clinical validation study with actual brain images of 10 human subjects, the average coefficient of variation between observers for the measurement of absolute brain and CSF volumes was 1.2% and 6.4%, respectively. The intraclass correlations for three expert operators is greater than .99 in the measurement of brain and ventricular volumes and greater than .94 for total CSF volume. Therefore, the authors believe that their technique to analyze MR images of the brain performed with acceptable levels of accuracy and reliability and that it can be used to measure brain and CSF volumes for clinical research. This technique could be helpful in the correlation of neuroanatomic measurements to behavioral and physiologic parameters in neuropsychiatric disorders.

Algorithms↗

PubMed1995

Toward an intelligent wound assessment system.

There is general agreement regarding the need for pressure ulcer assessment methodology which more discretely reflects relevant aspects of wound status than does the commonly used staging system. The Pressure Sore Status Tool (PSST) is one such instrument which was developed with consensual expert input. While the psychometric properties of the PSST have been reported in the literature, the instrument was validated using ET nurses, highly trained wound care specialists, and existed only in manual form. This paper reports results from attempts to establish reliability estimates for healthcare practitioners without extraordinary wound care training or experience. The paper further describes the automation of the PSST and provides examples of pressure ulcer profiles tracked over time. Results indicate that inter-rater reliability with general healthcare practitioners was .78 and intra-rater reliability was .89. The practitioners were able to use the PSST for over six months and the automated system allowed analysis of wound healing profiles that would have been difficult using a manual system. These results imply that movement toward an automated system which makes discriminations regarding the effects of various treatment and intervention strategies is possible and practical.

Aged↗

PubMed1994

The role of quality assurance in computer inspections.

Changing technology affords the Quality Assurance auditor with the challenge of applying computer validation concepts to a variety of computer system types. In addition, these technology changes have caused the developers role to change as well. In an innovative research facility, the developer may include an in-house professional group, a vendor, or an end-user. With these issues in mind, the QA auditor needs a tool to accomplish the task of inspecting systems as they are being created. The prospective inspection process is the tool for accomplishing this task. This inspection involves the QA auditor's involvement in the development of a new system, as a member of the development team, from the initial creation through the implementation of the computer system. This presentation will focus on illustrating the steps in conducting the prospective inspection process, from expected deliverables and document reviews to final report and management notification. The benefits of QA involvement in the development process will also be discussed.

Clinical Laboratory Information Systems↗

PubMedDate not supplied

Computerized decision support for concurrent utilization review using the HELP system.

OBJECTIVE: Development and evaluation of computerized concurrent utilization review (UR) support taking advantage of a clinically rich computerized patient database. DESIGN: The Automated Support System for Utilization Review (ASSURE) applies the Appropriateness Evaluation Protocol (AEP) Day of Care criteria to computerized patient data in the HELP hospital information system. This paper reports the development, verification, and validation of ASSURE. MEASUREMENTS: Implementation correctness was verified by measuring agreement with a nurse reviewer, using separate sample sets for all 20 criteria for a total of 560 current inpatients. Usefulness in detecting inappropriate days of care was validated by two nurse reviewers who were crossed with manual and computer-assisted review methods in a blocked design for 168 current inpatients. Agreement with reviewers, sensitivity, specificity, positive predictive value, and negative predictive value were measured. RESULTS: Agreement was very good for satisfaction of criteria, and good for appropriateness of day of care. A patient day identified by ASSURE as potentially inappropriate would be twice as likely to be judged inappropriate by a reviewer as a randomly selected patient day. Review of the 10% of patient days identified as potentially inappropriate by ASSURE would identify approximately 21% of the inappropriate days of care. CONCLUSION: ASSURE is a clinically useful tool for screening adult acute care patients for inappropriate days of care, and promises to make a major contribution to reducing health care costs. The prognosis for successful routine clinical use is good.

Artificial Intelligence↗

PubMedDate not supplied

A strategy for development of computerized critical care decision support systems.

It is not enough to merely manage medical information. It is difficult to justify the cost of hospital information systems (HIS) or intensive care unit (ICU) patient data management systems (PDMS) on this basis alone. The real benefit of an integrated HIS or PDMS is in decision support. Although there are a variety of HIS and ICU PDMS systems available there are few that provide ICU decision support. The HELP system at the LDS Hospital is an example of a HIS which provides decision support on many different levels. In the ICU there are decision support tools for antibiotic therapy, nutritional management, and management of mechanical ventilation. Computer protocols for the management of mechanical ventilation (respiratory evaluation, ventilation, oxygenation, weaning and extubation) in patients with adult respiratory distress syndrome ((ARDS) have already been developed and clinically validated at the LDS Hospital. These protocols utilize the bedside intensive care unit (ICU) computer terminal to prompt the clinical care team with therapeutic and diagnostic suggestions. The protocols (in paper flow diagram and computerized form) have been used for over 40,000 hours in more than 125 adult respiratory distress syndrome (ARDS) patients. The protocols controlled care for 94% of the time. The remainder of the time patient care was not protocol controlled was a result of the patient being in states not covered by current protocol logic (e.g. hemodynamic instability, or transport for X-Ray studies). 52 of these ARDS patients met extra corporal membrane oxygenation (ECMO) criteria. The survival of the ECMO criteria ARDS patients was 41%, four times that expected (9%) from historical data (p less than 0.0002).(ABSTRACT TRUNCATED AT 250 WORDS)

Attitude of Health Personnel↗

PubMedDate not supplied

The development of a comprehensive, institution-based patient risk evaluation program: II. Validity and reliability of questionnaire data.

The accuracy of historical information derived from self-administered questionnaires must be confirmed. We report the results of studies conducted to assess the reliability and validity of data collected from a comprehensive cancer risk factor questionnaire developed at The University of Texas M.D. Anderson Cancer Center. A comparison of the basic demographic data of a randomly selected sample of 80 respondents and 70 nonrespondents revealed no fundamental ethnic or socioeconomic differences. We verified self-reported past illnesses, surgical procedures, and cancers by reviewing 72 patient charts, using stringent diagnostic criteria for verification. We noted substantial agreement between self-reported and documented illnesses and operations. With the exception of nine patients who misclassified metastatic disease, the verification of primary cancers was excellent. We determined reliability by interviewing 50 of these patients by telephone. Questions with a dichotomous outcome (e.g., smoking status) were reliably answered; however, those requiring quantification (e.g., amount of alcohol consumed) were less accurately reported on interview. While we recognize the limitations of self-administered questionnaires, we believe this program will develop into a comprehensive, standardized, easily accessible patient risk factor data base.

Cancer Care Facilities↗