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Results for “Expert Systems”

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PubMed1992

Diagnosis of skeletal form on the lateral cephalogram with a finite element-based expert system.

Orthodontic diagnosis depends largely on the current methods of cephalometric analysis and categorization. It is therefore unfortunate that such analyses tend to use inappropriate metrical systems that lack a rigorous scientific basis. As a consequence, the resultant data have questionable validity, as well as being subject to observer bias. In this study, an alternative, more rigorous, approach is described. A random sample of 126 pretreatment lateral cephalograms were analyzed with the finite element method. These data were then classified to form a training set or reference data base for the subsequent objective diagnosis of new, previously unclassified cases. This new case-classification system was based on matching the new cases to similar cases within the existing training set. The degree of concordance between such computer-matched cases was then evaluated by their subsequent conventional cephalometric analyses.

Adolescent↗

PubMed1985

An expert system for nursing practice. Clinical decision support.

An artificial-intelligence-based nursing knowledge base can serve as an expert clinical decision support system in the areas of standards of care, care plans, continuing education, and others for patient conditions with both medical and nursing diagnoses.

Computers↗

PubMed1994

The rational selection of purification processes for proteins: an expert system for downstream processing design.

This paper describes the present state of the art in the use of ES for the rational selection of optimal purification processes for proteins (process synthesis). The main issues involved in selection of operations and process synthesis are reviewed. The high-resolution purification stages (one, two, three, or even more chromatographic steps where several alternatives in different orders of combinations can be used) have a combinatorial nature that can be represented by a "tree" structure. It can be analyzed by a depth-first or a breath-first approach. The two previous prototypes that have been developed are reviewed. The first prototype was exclusively based on "expert" rules, and its main weakness was in the selection of high-resolution purification operations for which a database of physicochemical properties of the main protein contaminants is needed. This was implemented in the second prototype in which a program for the calculation of separation coefficients on selection of high-resolution purification operations based on a preliminary database was interfaced. The present prototype being created uses a newly developed shell, which has an open architecture and uses object-oriented programming. This prototype uses a more "realistic" and accurate database (e.g., titration curves for contaminant proteins) and a tested method for selection of purification operations. The ES for selection of optimal protein separation sequences will give the user a number of alternatives chosen on the basis of the extensive data backup on proteins and unit operations.

Biotechnology↗

PubMedDate not supplied

Protein recovery, separation and purification. Selection of optimal techniques using an expert system.

The paper discusses the utilization of new techniques to select processes for protein recovery, separation and purification. It describes a rational approach that uses fundamental databases of protein molecules to simplify the complex problem of choosing high resolution separation methods for multi component mixtures. It examines the role of modern computer techniques to help solving these questions.

Biotechnology↗

PubMed2005

Modular expert system for the diagnosis of operating conditions of industrial anaerobic digestion plants.

Anaerobic digestion (AD) plants are highly efficient wastewater treatment processes with possible energetic valorisation. Despite these advantages, many industries are still reluctant to use them because of their instability in the face of changes in operating conditions. To the face this drawback and to enhance the industrial use of anaerobic digestion, one solution is to develop and to implement knowledge base (KB) systems that are able to detect and to assess in real-time the quality of operating conditions of the processes. Case-based techniques and heuristic approaches have been already tested and validated on AD processes but two major properties were lacking: modularity of the system (the knowledge base system should be easily tuned on a new process and should still work if one or more sensors are added or removed) and uncertainty management (the assessment of the KB system should remain relevant even in the case of too poor or conflicting information sources). This paper addresses these two points and presents a modular KB system where an uncertain reasoning formalism is used to combine partial and complementary fuzzy diagnosis modules. Demonstration of the interest of the approach is provided from real-life experiments performed on an industrial 2,000 m3 CSTR anaerobic digester.

Bacteria, Anaerobic↗

PubMedDate not supplied

An expert system based on the principle of the functional asymmetry of the brain.

A general concept for automating the secondary processing of data is proposed. Starting information is accumulated in a database. During processing, a textual description is generated for each object, and all further manipulations consists of transformations of the database. The use of this approach allows different types of information to be accumulated and analyzed efficiently using a single scheme.

Brain↗

PubMed1989

MAP, an expert system for multiple pairwise linkage analysis.

The logic of a program for multiple pairwise linkage analysis under interference is set forth, including a seriation algorithm to obtain a trial order, a mapping bootstrap to improve the trial order, and three procedures for quality control to detect mistyping. This approach is compared with multipoint analysis under null interference, which substantially overestimates map length and cannot incorporate a variety of data.

Algorithms↗

PubMed1998

A computer-based expert system designs and analyzes a 2(k - p) fractional factorial design for the formulation optimization of novel multicomponent liposomes.

A computer-based technique based on a 2(k - p) fractional factorial design was applied for the optimization of recently described multicomponent protective liposomal formulations. These formulations contain sodium ascorbate (vitamin C) as a model drug sensitive to photochemical oxidation, as well as oil red O and/or oxybenzone as oil soluble light absorbers, incorporated into the lipid bilayers and sulisobenzone as a water soluble light absorber incorporated into the aqueous phase of liposomes. The three light absorbers (present or absent) incorporated in multilamellar liposomes and the drug in free or in complexed with alpha-cyclodextrin form comprised the four factors of the system. The stabilization ratio and the percentage entrapment in the liposomes of the vitamin were the two response variables of the system to be optimized. The entrapment values were calculated for all the materials either spectrophotometrically or by using second order derivative spectrophotometry. The response variables were predicted by multiple regression equations comprising combinations of the four formulation factors. Both the higher entrapment and the higher protection for the drug should characterize the optimum formulation.

Chemistry, Pharmaceutical↗

PubMed2004

Integrating databases and expert systems for the analysis of brain structures: connections, similarities, and homologies.

The NeuroHomology Database system (NHDB) combines databases related to brain structures from different species with different knowledge management systems (KMSs) for systematization, evaluation and processing neurobiological data. Special attention is assessment of similarity of data from different species as a basis for exploring neural homologies. NHDB includes modules that handle brain structure and connectivity data, as well as inference engines for evaluation of the stored neurobiological information. The spatial inference engine evaluates the possible topological relations between cortical structures in different neuroanatomical atlases. The connectivity inference engine evaluates the reliability of information pertaining to fiber tracts as those are reflected in the literature. The inference engine for translation of neuroanatomical connections in different atlases evaluates the probability of existence of connections of interest in different parcellation schemes. Finally, the similarity inference engine calculates the overall degree of similarity of pairs of brain structures from different species by taking into account a set of eight criteria. We present examples of search for information in NHDB system, inferences of relations between cortical structures from equivalent neuroanatomical atlases, reconstruction of functional networks of brain structures from data collated from the literature, translation of connectivity matrices in equivalent parcellation schemes, and evaluations of similarities of brain structures from humans, macaques and rats.

Algorithms↗

PubMed1993

Uses of diagnostic expert systems in clinical care.

The development and testing of computerized systems to assist in the diagnostic process is a time honored research activity in medical information science. The focus of the majority of the applications produced is on providing accurate diagnostic suggestions when appropriate clinical information is entered. We believe that diagnostic knowledge has a much wider range of uses than that of simply assigning diagnostic labels. Below we describe three applications which illustrate alternate uses for diagnostic systems. Applications that assist in data collection, assess the quality of medical reports, and extract relevant clinical data from natural language x-ray reports are discussed. We believe that more effort should be directed toward studying the use of diagnostic knowledge bases in processes that help plan diagnostic strategies, in quality assurance applications, and in processes that facilitate all aspects of medical communication.

Clinical Medicine↗

PubMedDate not supplied

[An expert system for differentiation of viral meningitis].

The LOSTI system for viral meningitis differentiation, by using promptly accessible attributes, has been described. It is based on attribute values (averages and percentages). Logical principles on similarities and diversities are used. The system is dynamic for its ability to make itself permanently adjusted by using new cases and their attribute values. Through the possibility of prompt data processing according to a certain methodology, the system is able to take part in medical decision making. Its intention is not to make any definite decisions, just to "substitute" aetiologic diagnostics of viral meningitis in case it has not been successful or has not been done. It can also be used in epidemiological and statistical studies so long as the fact still stands that over half of the cases of serous meningitis remain aetiologically undiagnosed.

Diagnosis, Differential↗

PubMed1987

Bringing HELP to the clinical laboratory--use of an expert system to provide automatic interpretation of laboratory data.

In domains where the types of data which are to be interpreted are relatively constrained (as in the case of specific laboratory test results), our modular data-driven approach can be very productive and well received by the clinical recipient of the data. The computer rarely surpasses the knowledge of an experts result from lack of communication, imperfect memory, oversight or multiple decision-makers caring for the same patient. In such cases, most of the alerts are immediately recognized as valid, so the need for elaborate explanations is not a high priority. On the other hand, a non-specialist is alerted to the need for additional investigation, tests or collaborative support, by the fact that a reminder or diagnosis that s/he had not previously considered, appears. In other words, for the expert, a data-driven system provides unceasing oversight in high-volume low-yielded situations where a small number of mistakes may uncommonly occur for reasons which are not related to the lack of knowledge of the provider. For the non-specialist the system suggests that the patient may have problems in a domain for which the physician needs additional support. In the present state of the art, we do not think that total reliance on the computer-contained knowledge is the ultimate source of this additional support; providing the awareness of the need may be the most important contribution. Once you know that you need help, it is usually obtainable. In a discussion about how computer systems have failed, Friedman and Gustafson made the following observation.(ABSTRACT TRUNCATED AT 250 WORDS)

Decision Making, Computer-Assisted↗

PubMed1991

The expert system for toxicity prediction of chemicals based on structure-activity relationship.

The prediction systems of chemical toxicity has been developed by means of structure-activity relationship based on the computerized fact database (BL-DB). Numbers and ratio of elements, side chains, bonding, position, and microenvironment of side chains were used as structural factors of the chemical for the prediction. Such information was obtained from the BL-DB database by Wiswesser line-formula chemical notation. In the present study, the Salmonella/microsome assay was chosen as indicative of the target toxicity of chemicals. A set of chemicals specified with mutagenicity data was retrieved, and necessary information was extracted and transferred to the working file. Rules of the relations between characteristics of chemical structure and the assay result are extracted as parameters for rules by experts on the rearranged data set. These were analyzed statistically by the discriminant analysis and the prediction with the rules were evaluated by the elimination method. Eight kinds of rules to predict Salmonella/microsome assay were constructed, and currently results of the assay on aliphatic and heterocyclic compounds can be predicted as accurately as +90%.

Algorithms↗

PubMed2000

ProFound: an expert system for protein identification using mass spectrometric peptide mapping information.

We describe the protein search engine "ProFound", which employs a Bayesian algorithm to identify proteins from protein databases using mass spectrometric peptide mapping data. The algorithm ranks protein candidates by taking into account individual properties of each protein in the database as well as other information relevant to the peptide mapping experiment. The program consistently identifies the correct protein(s) even when the data quality is relatively low or when the sample consists of a simple mixture of proteins. Illustrative examples of protein identifications are provided.

Algorithms↗

PubMed1996

Sherpa: a Macintosh-based expert system for the interpretation of electrospray ionization LC/MS and MS/MS data from protein digests.

A computer program, Sherpa, has been implemented to aid in the elucidation of electrospray ionization liquid chromatography/mass spectrometry (LC/MS) and tandem mass spectrometry data from protein digests. The program differs from existing analysis software in its ability to search concurrently against multiple protein sequences, to search and compare two LC/MS files concurrently, to search for glycosylated and phosphorylated peptides, and to give a simple evaluation of the quality of a match between the data and a prediction.

Amino Acid Sequence↗

PubMedDate not supplied

The control of some viral epidemics by antiepidemic programmes elaborated by an expert system.

A base of data for viral epidemiological studies is presented containing correlation between outer symptoms (observable characteristics of the mass morbid phenomena), inner symptoms (characteristics of intensity of elementary processes implied in the virosis propagation) and influencing factors (risk or protective ones). A resolutive nucleus of processing these is divided in to three parts: an inductive one (specification of the mentioned correlations, of the mathematical model and its equation solutions); a deductive one (explaining or prognosing the epidemiological evolution); a decisional one (specifying the antiepidemic services, necessary for a possible or desired reduction of the morbidity).

Disease Outbreaks↗

PubMed1990

Computer-aided intelligence: application of an expert system to brachial plexus injuries.

When confronted with a patient with a brachial plexus injury, how often as neurosurgeons do we consult an atlas to confirm the anatomy of the brachial plexus and then attempt to establish the location of the lesion? Similar difficulties are encountered with lumbar and sacral plexus lesions. In a project organized to assist the neurosurgeon in this time-consuming task, a computer program that can rapidly determine the site of a lesion in a brachial, lumbar, or sacral plexus injury was created. Using known anatomical pathways (37 clinically relevant upper and 20 lower extremity muscle innervations), and relying solely upon the neurological motor examination, rapid computer-assisted diagnosis is possible. When more than one final common pathway lesion occurs (for example, multiple root avulsions of the brachial plexus), possible lesion sites can be obtained. An interactive dialogue between the user and the program helps to determine the location of the lesion. The program can be run on any IBM-compatible personal computer and is presented as an instrument that provides assistance in cases of complex peripheral nerve injuries, when expert consultants are unavailable. In addition, it can be used as an aid to learning and as a review of basic neuroanatomy.

Artificial Intelligence↗

PubMedDate not supplied

[Expert system for automatic, subjective determination of refraction].

An automatic system for determining a patient's subjective refraction for the fitting of glasses or contact lenses, is described. The system works without any intervention on the part of the ophthalmologist or optometrist. Directions are provided and questions asked of the patient via a loudspeaker or headphones with the aid of a computer. This computer also controls the positioning of different lenses before the patient's eyes using a phoropter, and the projection of the chart figures for visual acuity testing. The patient responds via a dedicated graphic tactile answering unit. The principles involved are described, and the experience so far gained with the method discussed.

Artificial Intelligence↗