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PubMed1997

A WWW-accessible knowledge base for the interpretation of hepatitis serologic tests.

HEPAXPERT is a knowledge-based system that interprets the results of routine serologic tests for infection with hepatitis A and B viruses. The following tests are included: hepatitis A virus anti-bodies (anti-HAV), IgM antibodies to the hepatitis A virus (IgM anti-HAV), hepatitis A virus (HAV in stool, hepatitis B surface antigen (HBsAg) and antibodies (qualitative anti-HBs, quantitative anti-HBs titre), antibodies to hepatitis B core antigen (anti-HBc and IgM anti-HBc), and hepatitis B envelope antigen (HBeAg) and antibodies (anti-HBe). HEPAXPERT/WWW--an implementation of HEPAXPERT-III for WWW--can be reached by URL http://www.swun.com/hepax of the World Wide Web. After selecting HEPAXPERT/WWW, serologic test results can be entered and will be transferred as an e-mail message for subsequent interpretation which is done off-line with HEPAXPERT-III. The textual interpretation is sent back via e-mail. Each qualitative test for hepatitis A and B antibodies and antigens may produce one of four possible results: positive, negative, borderline, and not tested. To cover the resulting 64 (A) and 57344 (B) combinations of findings, the knowledge base of HEPAXPERT/WWW contains 16 rules for hepatitis A and 131 rules for hepatitis B serology interpretation. This basic knowledge is structured such that all possible combinations of findings can be interpreted and there is no overlap in the premises underlying the rules. The reports that the system automatically generates include: (a) the transferred results of the tests; (b) a detailed analysis of the results, including virus exposure, immunity, stage of illness, prognosis, infectiousness, and vaccination recommendation; and (c) optional: an ID to distinguish the origin of the interpretation requests.

Artificial Intelligence↗

PubMed1982

An experimental transformation of a large expert knowledge base.

An experiment is described in which a significant part of the INTERNIST knowledge base for diagnosis in internal medicine is translated into an EXPERT model. INTERNIST employs the largest and broadest knowledge base of all the medical consultation systems that have been developed in recent years. EXPERT is a general system for designing consultation models. The translated model shows reasonable competence in the final diagnostic classification of 431 test cases. There are differences in the internal representation and reasoning relatively uniform manner, this experiment demonstrates the feasibility of transfer of knowledge between large-scale expert systems.

Diagnosis, Computer-Assisted↗

PubMedDate not supplied

Knowledge-based quality management and clinical pathways.

OBJECTIVES: Although 65% of the hospitals in Taiwan claim to be applying the clinical pathway concept, most hospitals do not implement this concept effectively. The purpose of this study was to determine the reasons for the improper or inappropriate application of the clinical pathway design in hospitals. METHODS: This study differs from other studies in clinical pathway design and application in that it seeks to resolve misunderstandings of the clinical pathway analysis that may have been generated by the responses to survey questionnaires. Therefore, in-depth interviews and Senge's system archetype have been used to ascertain the reasons why the use of a clinical pathway design has been ineffective. We also used the 4 dimensions of knowledge-based management proposed by Drucker to set up the knowledge-based clinical pathway. Thirteen experts used the Delphi method to construct 20 knowledge-based clinical pathway guidelines. CONCLUSIONS: The application of knowledge- and management-based clinical pathway designs is recommended.

Critical Pathways↗

PubMed2005

Knowledge base version reintegration.

Given two versions of a knowledge base (KB), independently modified, we investigated the problem of incorporating changes made to one KB version into the other. We have implemented a system that will perform such a reintegration, autonomously, using predetermined user preferences. This effort has lead to a greater insight into the version reintegration problem and has highlighted those areas where user intervention would be the most beneficial in a semi-autonomous system.

Anatomy↗

PubMed2004

Knowledge-based elastic potentials for docking drugs or proteins with nucleic acids.

Elastic ellipsoidal functions defined by the observed hydration patterns around the DNA bases provide a new basis for measuring the recognition of ligands in the grooves of double-helical structures. Here a set of knowledge-based potentials suitable for quantitative description of such behavior is extracted from the observed positions of water molecules and amino acid atoms that form hydrogen bonds with the nitrogenous bases in high resolution crystal structures. Energies based on the displacement of hydrogen-bonding sites on drugs in DNA-crystal complexes relative to the preferred locations of water binding around the heterocyclic bases are low, pointing to the reliability of the potentials and the apparent displacement of water molecules by drug atoms in these structures. The validity of the energy functions has been further examined in a series of sequence substitution studies based on the structures of DNA bound to polyamides that have been designed to recognize the minor-groove edges of Watson-Crick basepairs. The higher energies of binding to incorrect sequences superimposed (without conformational adjustment or displacement of polyamide ligands) on observed high resolution structures confirm the hypothesis that the drug subunits associate with specific DNA bases. The knowledge-based functions also account satisfactorily for the measured free energies of DNA-polyamide association in solution and the observed sites of polyamide binding on nucleosomal DNA. The computations are generally consistent with mechanisms by which minor-groove binding ligands are thought to recognize DNA basepairs. The calculations suggest that the asymmetric distributions of hydrogen-bond-forming atoms on the minor-groove edge of the basepairs may underlie ligand discrimination of G.C from C.G pairs, in addition to the commonly believed role of steric hindrance. The analysis of polyamide-bound nucleosomal structures reveals other discrepancies in the expected chemical design, including unexpected contacts to DNA and modified basepair targets of some ligands. The ellipsoidal potentials thus appear promising as a mathematical tool for the study of drug- and protein-DNA interactions and for gaining new insights into DNA-binding mechanisms.

Algorithms↗

PubMed2002

AIDA--experiences in compensating the mutual weaknesses of knowledge-based and object-oriented development in a complex dental planning domain.

OBJECTIVES: Dentistry is a discipline with two properties that pose a serious challenge to knowledge based decision support: (1) It has to integrate six subdisciplines ranging from conservative measures to invasive disciplines, such as implantology; (2) A plan may have to cover a complex treatment often lasting one year or more. It is the aim of the AIDA-project to set up a planning strategy that is suited to incorporate all dental peculiarities in one methodology. METHODS: Generic tasks, that can be assigned to individual persons involved in dental treatment, have been designed with the help of KADS. They have been integrated into a planning super-structure for the planning of all dental solution alternatives, that can principally be applied on the basis of the given patient status. RESULTS: Besides an evaluation of the implemented planning system itself, it has been evaluated how well the development is supported by (1) knowledge-engineering methods and (2) object-oriented methods. CONCLUSION: Common knowledge-based tools are not powerful enough for the planning of complex dental constructions. Therefore, a solution combining object-oriented and knowledge-based methods is proposed.

Artificial Intelligence↗

PubMed1990

Integrating knowledge-based technology into computer aided ventilation systems.

A knowledge-based decision support system for respirator treatment, the KUSIVAR system, has been designed in cooperation between hospital, university and industry. Changes in patient data from respirator and monitoring equipment trigger a computer program that generates advice to the staff concerning e.g. therapy modes and respirator settings using expert systems and process control technology. A prototype has been built on an advanced development workstation, the Unisys Explorer, using the software Knowledge Engineering Environment (KEE). The clinical version is implemented on an Intel 80396-based microcomputer connected on-line via a data-acquisition processor to the respirator. The decision support software is implemented as a module under the Microsoft Windows multitasking environment and communicates with modules for data acquisition, database handling and data presentation by means of message passing using the Windows Dynamic Data Exchange protocol. The modules present coherent user interfaces by conforming to Microsoft Windows standards. The knowledge base is being extensively validated by an expert group in the ICU and the system will be evaluated through animal experiments and clinical studies.

Computer Systems↗

PubMed1996

HinCyc: a knowledge base of the complete genome and metabolic pathways of H. influenzae.

We present a methodology for predicting the metabolic pathways of an organism from its genomic sequence by reference to a knowledge base of known metabolic pathways. We applied these techniques to the genome of H. influenzae by reference to the EcoCyc knowledge base to predict which of 81 metabolic pathways of E. coli are found in H. influenzae. The resulting prediction is a complex hypothesis that is presented in computer form as HinCyc: an electronic encyclopedia of the genes and metabolic pathways of H. influenzae. HinCyc connects the predicted genes, enzymes, enzyme-catalyzed reactions, and biochemical pathways in a WWW-accessible knowledge base to allow scientists to explore this complex hypothesis.

Computer Communication Networks↗

PubMed1985

QUICK (QUick Index to Caduceus Knowledge): using the INTERNIST-1/CADUCEUS knowledge base as an electronic textbook of medicine.

QUICK (QUick Index to Caduceus Knowledge), is a prototypical user-friendly access system which adapts the INTERNIST-1/CADUCEUS knowledge base for use as an electronic textbook of medicine. The QUICK program can be used both as a diagnostic aid and a teaching tool in the field of internal medicine. A preliminary evaluation of a prototypical version of QUICK was conducted in order to identify its strengths and weaknesses. QUICK was made available to the medical housestaff at three Pittsburgh area teaching hospitals for a period of 2 months. Most users felt QUICK was educational and wanted future access to the system. An examination of log files revealed the users' most frequently encountered difficulties. Using the INTERNIST-I knowledge base as an electronic textbook expands the project's intended audience by providing clinical support for a broad group of diagnostic problems.

Computer-Assisted Instruction↗

PubMed1998

MHCWeb: converting a WWW database into a knowledge-based collaborative environment.

The World Wide Web (WWW) is useful for distributing scientific data. Most existing web data resources organize their information either in structured flat files or relational databases with basic retrieval capabilities. For databases with one or a few simple relations, these approaches are successful, but they can be cumbersome when there is a data model involving multiple relations between complex data. We believe that knowledge-based resources offer a solution in these cases. Knowledge bases have explicit declarations of the concepts in the domain, along with the relations between them. They are usually organized hierarchically, and provide a global data model with a controlled vocabulary. We have created the OWEB architecture for building online scientific data resources using knowledge bases. OWEB provides a shell for structuring data, providing secure and shared access, and creating computational modules for processing and displaying data. In this paper, we describe the translation of the online immunological database MHCPEP into an OWEB system called MHCWeb. This effort involved building a conceptual model for the data, creating a controlled terminology for the legal values for different types of data, and then translating the original data into the new structure. The OWEB environment allows for flexible access to the data by both users and computer programs.

Artificial Intelligence↗

PubMed1997

THEMPO: a knowledge-based system for therapy planning in pediatric oncology.

This article describes the knowledge-based system THEMPO (Therapy Management in Pediatric Oncology), which supports protocol-directed therapy planning and configuration in pediatric oncology. THEMPO provides a semantic network controlled by graph grammars to cover the different types of knowledge relevant in the domain, and offers a suite of acquisition tools for knowledge base authoring. Medical problem solvers, operating on the oncological network, reason about adequate therapeutic and diagnostic timetables for a patient. Furthermore, a corresponding patient record, also based on semantic networks and graph grammars, has been implemented to represent the course of therapy of an oncological patient.

Antineoplastic Combined Chemotherapy Protocols↗

PubMed2001

Knowledge-based potential defined for a rotamer library to design protein sequences.

A knowledge-based potential for a rotamer library was developed to design protein sequences. Protein side-chain conformations are represented by 56 templates. Each of their fitness to a given structural site-environment is evaluated by a combined function of the three knowledge-based terms, i.e. two-body side-chain packing, one-body hydration and local conformation. The number of matches between the native sequence and the structural site-environment in the database and that of the virtually settled mismatches, counted in advance, were transformed into the energy scores. In the best-14 test (assessment for the reproduction ability of the native rotamer on its structural site within a quarter of 56 fitness rank positions), the structural stability analysis on mutants of human and T4 lysozymes and the inverse-folding search by a structure profile against the sequence database, this function performs better than the function deduced with the conventional normalization and our previously developed function. Targeting various structural motifs, de novo sequence design was conducted with the function. The sequences thus obtained exhibit reasonable molecular masses and hydrophobic/hydrophilic patterns similar to the native sequences of the target and act as if they were the homologs to the target proteins in BLASTP search. This significant improvement is discussed in terms of the reference state for normalization and the crucial role of short-range repulsion to prohibit residue bumps.

Amino Acid Sequence↗

PubMed1994

Knowledge-based protein modeling.

Knowledge, both from the three-dimensional structures of homologous proteins and from the general analysis of protein structure, is of value in modeling a protein of known sequence but unknown structure. While many models are still constructed at least in part by manual methods on graphics devices, automated procedures have come into greater use. These procedures include those that assemble fragments of structure from other known structures and those that derive coordinates for the model from the satisfaction of restraints placed on atomic positions.

Amino Acid Sequence↗

PubMed1995

Integrated development of a knowledge-based CPR system for quality assurance in diabetes outpatient clinics.

Many approaches for the development of computer-based patient record (CPR) systems consider only implicitly the inferences a user wants to accomplish in using the system. However, the integration of knowledge-based support into the routine work flow requires an explicit model of the inferences during routine work. Such a model helps to structure the interface of the system and to identify those inference steps which could benefit from knowledge-based support. This paper describes the approach used in developing a CPR system taking into account its future role as a platform for the integration of knowledge bases into routine work.

Ambulatory Care Facilities↗

PubMed1993

Integrating knowledge-based systems and databases.

In recent years, there has been an explosion of interest among the computing community in the field of artificial intelligence, particularly in the areas of natural language processing and knowledge-based systems (KBS). The medical domain has seen the development of hundreds of KBSs and there is substantial evidence to show that the application of a knowledge-based approach to decision support can go a long way towards overcoming the information overload experienced by many clinicians today. Yet many of these medical KBSs are still at the prototype stage and are mainly confined to research laboratories. There are many reasons for this apparently slow take-up of the technology, but one of the most significant is the lack of integration into the regular routine information processing of the organisation, in particular the database processing. This paper discusses the benefits of such integration and methods for achieving it in the context of general trends in information systems. Database technology provides efficient and secure management of large amounts of data in a multi-user, multi-application environment. Knowledge-based technology, on the other hand, provides mechanisms for building intelligent systems. Thus, for example, given a set of facts about a domain (symptoms, laboratory test results, etc.) together with a set of rules which apply to that domain (e.g. 'if TT4 > 150 nmol/l then suspect hyperthyroidism'), a KBS can deduce new information about that domain automatically. The effective integration of these two technologies is seen as a means of achieving the intelligent information systems of the future. There are three basic approaches to integrating KBSs and databases. The first is to start with the KBS and incorporate data management functions. Alternatively, intelligence from the KBS can be incorporated into the database. Finally, the two systems can be allowed to co-exist as independent systems which can talk to each other by means of standard interfaces. There are many advantages to this last approach since it offers much more flexibility and extensibility and is consistent with the general trend in computing towards open systems.

Artificial Intelligence↗

PubMed2002

DrugScore meets CoMFA: adaptation of fields for molecular comparison (AFMoC) or how to tailor knowledge-based pair-potentials to a particular protein.

The development of a new tailor-made scoring function to predict binding affinities of protein-ligand complexes is described. Knowledge-based pair-potentials are specifically adapted to a particular protein by considering additional ligand-based information. The formalism applied to derive the new function is similar to the well-known CoMFA approach, however, the fields used in the approach originate from the protein environment (and not from the aligned ligands as in CoMFA, thus, a "reverse" CoMFA (= AFMoC) named Adaptation of Fields for Molecular Comparison is performed). A regular-spaced grid is placed into the binding site and knowledge-based pair-potentials between protein atoms and ligand atom probes are mapped onto the grid intersections resulting in "potential fields". By multiplying distance-dependent atom-type properties of actual ligands docked into the binding site with the neighboring grid values, "interaction fields" are produced from the original "potential fields". In a PLS analysis, these atom-type specific interaction fields are correlated to the actual binding affinities of the embedded ligands, resulting in individual weighting factors for each field value. As in CoMFA, the results of the analysis can be interpreted in graphical terms by contribution maps, and binding affinities of novel ligands are predicted by applying the derived 3D QSAR equation. The scope of the new method is demonstrated using thermolysin and glycogen phosphorylase b as test examples. Impressive improvements of the predictive power for affinity prediction can be achieved compared to the application of the original knowledge-based potentials by considering a sample set of only 15 known training ligands. Thus, with growing information about the drug target studied, the new method allows one to move gradually from generally valid to protein-specifically adapted pair-potentials, depending on the amount of training information available and its degree of structural diversity. In addition, convincing predictive power is also achieved for ligand poses generated by automatic docking tools.

Databases, Factual↗

PubMed1999

A JAVA implementation of a medical knowledge base for decision support.

Distributed decision support is a challenging issue requiring the implementation of advanced computer science techniques together with tools of development which offer ease of communication and efficiency of searching and control performance. This paper presents a JAVA implementation of a knowledge base model called ARISTOTELES which may be used in order to support the development of the medical knowledge base by clinicians in diverse specialised areas of interest. The advantages that are evident by the application of such a cognitive model are ease of knowledge acquisition, modular construction of the knowledge base and greater acceptance from clinicians.

Artificial Intelligence↗

PubMed1989

GENPRO: automatic generation of Prolog clause files for knowledge-based systems in the biomedical sciences.

With the increasing interest in using knowledge-based approaches for protein structure prediction and modelling, there is a requirement for general techniques to convert molecular biological data into structures that can be interpreted by artificial intelligence programming languages (e.g. Prolog). We describe here an interactive program that generates files in Prolog clausal form from the most commonly distributed protein structural data collections. The program is flexible and enables a variety of clause structures to be defined by the user through a general schema definition system. Our method can be extended to include other types of molecular biological database or those containing non-structural information, thus providing a uniform framework for handling the increasing volume of data available to knowledge-based systems in biomedicine.

Database Management Systems↗