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PubMed1996

Improved monitoring of preterm infants by Fuzzy Logic.

Keeping the oxygenation status of newborn infants within physiologic limits is a crucial task in intensive care. For this purpose several vital parameters are supervised routinely by monitors, such as electrocardiograph, transcutaneous partial oxygen pressure monitor and pulse oximeter. Each monitor issues an alarm signal whenever an upper or lower limit of the parameter(s) measured is exceeded. However, in practice it turns out, that a considerable amount of false alarms is generated by artefacts, which are attributed mostly to movements of the infants. Eliminating these false alarms would be of benefit to the staff as well as the patients of the intensive care unit. Accordingly, an automated system based on Fuzzy Logic was developed, which is capable of distinguishing between critical situations and artefacts. The system is based on a Transputer IMS T425 in a PC, which collects the data from the monitors, plots it on a colour screen, saves it to hard disk and analyses it by Fuzzy Logic. Fuzzy algorithms were developed to generate more reliable alarms. All vital parameters of eight infants, who either moved often and/or frequently produced real alarm situations, were recorded. Synchronously the infants' movements and care procedures were video taped. The data and video were analysed off line with the help of an experienced neonatologist. His judgement was compared to the analysis of the Fuzzy Logic system. The results show that it is possible to improve the reliability of the monitored data with the aid of an evaluation strategy based on Fuzzy Logic and hence distinguish between real alarm situations and movement artefacts to the extent that an application in an intensive care unit under routine conditions becomes conceivable.

Algorithms↗
PubMed1998

Understanding of logical necessity: developmental antecedents and cognitive consequences.

Does abstract reasoning develop naturally, and does instruction contribute to its development? In an attempt to answer these questions, this article specifically focuses on effects of prolonged instruction on the development of abstract deductive reasoning and, more specifically, on the development of understanding of logical necessity. It was hypothesized that instructional emphasis on the metalevel of deduction within a knowledge domain can amplify the development of deductive reasoning both within and across this domain. The article presents 2 studies that examine the development of understanding of logical necessity in algebraic and verbal deductive reasoning. In the first study, algebraic and verbal reasoning tasks were administered to 450 younger and older adolescents selected across different instructional settings in England and in Russia. In the second study, algebraic and verbal reasoning tasks were administered to 287 Russian younger and older adolescents selected across different instructional settings. The results support the hypothesis, indicating that prolonged instruction with an emphasis on the metalevel of algebraic deduction contributes to the development of understanding of logical necessity in both algebraic and verbal deductive reasoning. Findings also suggest that many adolescents do not develop an understanding of logical necessity naturally.

Adolescent↗
PubMed2005

Identifying interacting SNPs using Monte Carlo logic regression.

Interactions are frequently at the center of interest in single-nucleotide polymorphism (SNP) association studies. When interacting SNPs are in the same gene or in genes that are close in sequence, such interactions may suggest which haplotypes are associated with a disease. Interactions between unrelated SNPs may suggest genetic pathways. Unfortunately, data sets are often still too small to definitively determine whether interactions between SNPs occur. Also, competing sets of interactions could often be of equal interest. Here we propose Monte Carlo logic regression, an exploratory tool that combines Markov chain Monte Carlo and logic regression, an adaptive regression methodology that attempts to construct predictors as Boolean combinations of binary covariates such as SNPs. The goal of Monte Carlo logic regression is to generate a collection of (interactions of) SNPs that may be associated with a disease outcome, and that warrant further investigation. As such, the models that are fitted in the Markov chain are not combined into a single model, as is often done in Bayesian model averaging procedures. Instead, the most frequently occurring patterns in these models are tabulated. The method is applied to a study of heart disease with 779 participants and 89 SNPs. A simulation study is carried out to investigate the performance of the Monte Carlo logic regression approach.

Haplotypes↗
PubMed2003

Logical inconsistencies in survey respondents' health state valuations -- a methodological challenge for estimating social tariffs.

Logical inconsistencies in survey respondents' valuations of hypothetical health states - represented by the EQ-5D, for example - present a conundrum as to whether or not their responses ought to be included for estimating social 'tariffs'. A 'logical inconsistency' occurs when a state that 'in logical terms' is unambiguously less severe than another is assigned a lower value. Excluding such responses is defensible on data quality grounds but puts at risk the representativeness of the estimated tariff, given it is meant to represent the preferences of 'society'. This paper explores the rationale for and effect of excluding, to varying degrees, responses distinguished by the number of pairwise inconsistencies they contain, and reports equations for two tariffs that arise from contrasting approaches. The data are from a random sample of adult New Zealanders whose visual analogue scale valuations for a selection of EQ-5D states were collected in 1999 via a postal survey to which 1360 people responded (a 50% response rate). We conclude that there is no simple, generalisable 'rule' to guide exclusions and therefore researchers ought to explore the sensitivity of their estimated tariffs (and ultimately QALY estimates) to alternative treatments of logically inconsistent responses.

Adolescent↗
PubMed1991

Medical logic module (MLM) representation of knowledge in a ventilator treatment advisory system.

In any medical expert system it is the inherent knowledge that is the power of the system and not the particulars of its implementation. Therefore it would be valuable to use a representation that would allow: knowledge transfer between different systems, users, experts and 'importers' to be able to evaluate the logic, experts to easily input their knowledge and be guided how to use the syntax. Adren Syntax of Medical Logic Module is a proposed knowledge representation, fulfilling these criteria. The Arden Syntax has been used to represent rules and logic in a decision support system for ventilator therapy in patients with acute respiratory failure (ARF) that is under development. The medical experts involved in the project have used the Arden Syntax as a convenient way for transfer and storage of medical knowledge. The syntax is easy to learn and may be used with a minimum of training. In the present system, Medical Logical Modules have been used to represent knowledge pertinent to the initiation and maintenance phases of ventilator therapy.

Acute Disease↗
PubMed1999

A biomolecular implementation of logically reversible computation with minimal energy dissipation.

Energy dissipation associated with logic operations imposes a fundamental physical limit on computation and is generated by the entropic cost of information erasure, which is a consequence of irreversible logic elements. We show how to encode information in DNA and use DNA amplification to implement a logically reversible gate that comprises a complete set of operators capable of universal computation. We also propose a method using this design to connect, or 'wire', these gates together in a biochemical fashion to create a logic network, allowing complex parallel computations to be executed. The architecture of the system permits highly parallel operations and has properties that resemble well known genetic regulatory systems.

Animals↗
PubMed2003

DNA-based photonic logic gates: AND, NAND, and INHIBIT.

Conventional microprocessors use elementary logic gates to perform complex computational tasks. Mimicking such computational processes using purely molecular systems has been limited in most cases by the lack of design generality or potential addressability of existing molecular logic gates. Herein we report that by employing the universal recognition properties of DNA simple photonic logic gates can be created that are capable of AND, NAND, and INHIBIT logic operations.

Computational Biology↗
PubMed1999

Total system performance assessment for waste disposal using a logic tree approach.

The Electric Power Research Institute (EPRI) has sponsored the development of a model to assess the long-term, overall "performance" of the candidate spent fuel and high-level radioactive waste (HLW) disposal facility at Yucca Mountain, Nevada. The model simulates the processes that lead to HLW container corrosion, HLW mobilization from the spent fuel, and transport by groundwater, and contaminated groundwater usage by future hypothetical individuals leading to radiation doses to those individuals. The model must incorporate a multitude of complex, coupled processes across a variety of technical disciplines. Furthermore, because of the very long time frames involved in the modeling effort (>> 10(4) years), the relative lack of directly applicable data, and many uncertainties and variabilities in those data, a probabilistic approach to model development was necessary. The developers of the model chose a logic tree approach to represent uncertainties in both conceptual models and model parameter values. The developers felt the logic tree approach was the most appropriate. This paper discusses the value and use of logic trees applied to assessing the uncertainties in HLW disposal, the components of the model, and a few of the results of that model. The paper concludes with a comparison of logic trees and Monte Carlo approaches.

Geological Phenomena↗
PubMed2006

Multiargument logical operations performed with excitable chemical medium.

Assuming that a pulse of excitation corresponds to the logical "true" state one can use a chemical medium for information processing and construct devices that execute the basic binary logical operations. Here we discuss direct chemical realizations of four argument logical functions equivalent to special types of McCulloch-Pitts neuron. We demonstrate that if a proper geometrical arrangement of excitable and nonexcitable areas is used then the construction of the considered devices can be much simpler than in the case where they are composed of chemical binary logical gates.

Journal Article↗
PubMed1997

Using automated analysis of the resting twelve-lead ECG to identify patients at risk of developing transient myocardial ischaemia--an application of an adaptive logic network.

The aim of this study was to introduce an adaptive logic network computing method for detecting patients who were likely to show transient ischaemic episodes during ambulatory Holter monitoring, using parameters from a previously recorded standard twelve-lead resting electrocardiogram (ECG). In the present study, the adaptive logic network computing method is compared with other commonly used classification methods, such as backpropagation network and discriminant analysis techniques. Of 1367 study subjects aged 65 and above, 733 were women and 634 were men. Ambulatory Holter recordings were made to detect episodic ischaemia in study patients. Those subjects showing ischaemic episodes were classified as 'ischaemic' patients, and the remaining subjects were 'non-ischaemic'. Accuracy was 67% using the adaptive logic network computing method, 56% using the backpropagation network computing method, and 65% using statistical discriminant analysis. We concluded that the adaptive logic network technique offers a slightly higher accuracy and shows several potential advantages for automated detection of ischaemia in resting electrocardiograms.

Adult↗
PubMed1991

The application of SSADM to modelling the logical structure of proteins.

A logical design that describes the overall structure of proteins, together with a more detailed design describing secondary and some supersecondary structures, has been constructed using the computer-aided software engineering (CASE) tool, Auto-mate. Auto-mate embodies the philosophy of the Structured Systems Analysis and Design Method (SSADM) which enables the logical design of computer systems. Our design will facilitate the building of large information systems, such as databases and knowledgebases in the field of protein structure, by the derivation of system requirements from our logical model prior to producing the final physical system. In addition, the study has highlighted the ease of employing SSADM as a formalism in which to conduct the transferral of concepts from an expert into a design for a knowledge-based system that can be implemented on a computer (the knowledge-engineering exercise). It has been demonstrated how SSADM techniques may be extended for the purpose of modelling the constituent Prolog rules. This facilitates the integration of the logical system design model with the derived knowledge-based system.

Amino Acid Sequence↗
PubMed1998

Decision support and disease management: a logic engineering approach.

This paper describes the development and application of PROforma, a unified technology for clinical decision support and disease management. Work leading to the implementation of PROforma has been carried out in a series of projects funded by European agencies over the past 13 years. The work has been based on logic engineering, a distinct design and development methodology that combines concepts from knowledge engineering, logic programming, and software engineering. Several of the projects have used the approach to demonstrate a wide range of applications in primary and specialist care and clinical research. Concurrent academic research projects have provided a sound theoretical basis for the safety-critical elements of the methodology. The principal technical results of the work are the PROforma logic language for defining clinical processes and an associated suite of software tools for delivering applications, such as decision support and disease management procedures. The language supports four standard objects (decisions, plans, actions, and enquiries), each of which has an intuitive meaning with well-understood logical semantics. The development toolset includes a powerful visual programming environment for composing applications from these standard components, for verifying consistency and completeness of the resulting specification and for delivering stand-alone or embeddable applications. Tools and applications that have resulted from the work are described and illustrated, with examples from specialist cancer care and primary care. The results of a number of evaluation activities are included to illustrate the utility of the technology.

Decision Support Systems, Clinical↗
PubMed1999

Digital logic gate using quantum-Dot cellular automata

A functioning logic gate based on quantum-dot cellular automata is presented, where digital data are encoded in the positions of only two electrons. The logic gate consists of a cell, composed of four dots connected in a ring by tunnel junctions, and two single-dot electrometers. The device is operated by applying inputs to the gates of the cell. The logic AND and OR operations are verified using the electrometer outputs. Theoretical simulations of the logic gate output characteristics are in excellent agreement with experiment.

Journal Article↗
PubMedDate not supplied

Evaluation of a "lexically assign, logically refine" strategy for semi-automated integration of overlapping terminologies.

OBJECTIVE: To evaluate a "lexically assign, logically refine" (LALR) strategy for merging overlapping healthcare terminologies. This strategy combines description logic classification with lexical techniques that propose initial term definitions. The lexically suggested initial definitions are manually refined by domain experts to yield description logic definitions for each term in the overlapping terminologies of interest. Logic-based techniques are then used to merge defined terms. METHODS: A LALR strategy was applied to 7,763 LOINC and 2,050 SNOMED procedure terms using a common set of defining relationships taken from the LOINC data model. Candidate value restrictions were derived by lexically comparing the procedure's name with other terms contained in the reference SNOMED topography, living organism, function, and chemical axes. These candidate restrictions were reviewed by a domain expert, transformed into terminologic definitions for each of the terms, and then algorithmically classified. RESULTS: The authors successfully defined 5,724 (73%) LOINC and 1,151 (56%) SNOMED procedure terms using a LALR strategy. Algorithmic classification of the defined concepts resulted in an organization mirroring that of the reference hierarchies. The classification techniques appropriately placed more detailed LOINC terms underneath the corresponding SNOMED terms, thus forming a complementary relationship between the LOINC and SNOMED terms. DISCUSSION: LALR is a successful strategy for merging overlapping terminologies in a test case where both terminologies can be defined using the same defining relationships, and where value restrictions can be drawn from a single reference hierarchy. Those concepts not having lexically suggested value restrictions frequently indicate gaps in the reference hierarchy.

Algorithms↗
PubMed1997

Evolutionary program induction directed by logic grammars

Program induction generates a computer program that can produce the desired behavior for a given set of situations. Two of the approaches in program induction are inductive logic programming (ILP) and genetic programming (GP). Since their formalisms are so different, these two approaches cannot be integrated easily, although they share many common goals and functionalities. A unification will greatly enhance their problem-solving power. Moreover, they are restricted in the computer languages in which programs can be induced. In this paper, we present a flexible system called LOGENPRO (The LOgic gramar-based GENetic PROgramming system) that uses some of the techniques of GP and ILP. It is based on a formalism of logic grammars. The system applies logic grammars to control the evolution of programs in various programming languages and represent context-sensitive information and domain-dependent knowledge. Experiments have been performed to demonstrate that LOGENPRO can emulate GP and GP with automatically defined functions (ADFs). Moreover, LOGENPRO can employ knowledge such as argument types in a unified framework. The experiments show that LOGENPRO has superior performance to that of GP and GP with ADFs when more domain-dependent knowledge is available. We have applied LOGENPRO to evolve general recursive functions for the even-n-parity problem from noisy training examples. A number of experiments have been performed to determine the impact of domain-specific knowledge and noise in training examples on the speed of learning.

Journal Article↗
PubMed2006

Visual setup of logical models of signaling and regulatory networks with ProMoT.

BACKGROUND: The analysis of biochemical networks using a logical (Boolean) description is an important approach in Systems Biology. Recently, new methods have been proposed to analyze large signaling and regulatory networks using this formalism. Even though there is a large number of tools to set up models describing biological networks using a biochemical (kinetic) formalism, however, they do not support logical models. RESULTS: Herein we present a flexible framework for setting up large logical models in a visual manner with the software tool ProMoT. An easily extendible library, ProMoT's inherent modularity and object-oriented concept as well as adaptive visualization techniques provide a versatile environment. Both the graphical and the textual description of the logical model can be exported to different formats. CONCLUSION: New features of ProMoT facilitate an efficient set-up of large Boolean models of biochemical interaction networks. The modeling environment is flexible; it can easily be adapted to specific requirements, and new extensions can be introduced. ProMoT is freely available from http://www.mpi-magdeburg.mpg.de/projects/promot/.

Animals↗
PubMed2006

Simple online recognition of optical data strings based on conservative optical logic.

Optical packet switching relies on the ability of a system to recognize header information on an optical signal. Unless the headers are very short with large Hamming distances, optical correlation fails and optical logic becomes attractive because it can handle long headers with Hamming distances as low as 1. Unfortunately, the only optical logic gates fast enough to keep up with current communication speeds involve semiconductor optical amplifiers and do not lend themselves to the incorporation of large numbers of elements for header recognition and would consume a lot of power as well. The ideal system would operate at any bandwidth with no power consumption. We describe how to design and build such a system by using passive optical logic. This too leads to practical problems that we discuss. We show theoretically various ways to use optical interferometric logic for reliable recognition of long data streams such as headers in optical communication. In addition, we demonstrate one particularly simple experimental approach using interferometric coinc gates.

Journal Article↗
PubMed1985

Logic and empiricism in the selection of antiarrhythmic agents. The role of drug combinations.

Advances in investigative techniques of cardiac arrhythmias through invasive procedures (clinical electrophysiology) or through ambulatory electrocardiographic monitoring provide a better understanding of the mechanism responsible for these disturbances and a better assessment of therapeutic efficacy. Yet, it cannot be inferred that the selection of antiarrhythmic agents is orientated in all cases by logical reasoning. Too many factors are unknown, especially those regarding the spontaneous mechanism of initiation of clinical arrhythmias. Patient management very often remains mainly empirical. The problem becomes even more complex when dealing with arrhythmias resistant to single-agent therapy. Drug combinations are then used, often successfully, particularly those combining membrane-stabilising agents with amiodarone or beta-adrenergic blocking agents or combining amiodarone with verapamil. Explanations of the efficacy of these combinations at reduced doses become less certain, but it is more important to achieve efficacy than to understand its mechanism, which does not always amount to a simple increase in plasma drug levels. When attempting to determine the reasons behind the theoretically logical selection of an antiarrhythmic agent, it appears that, in spite of advances in electrophysiology and pharmacology, the logic of this selection owes more to chance than to reason. The problem becomes further complicated when drug combinations are to be used which, in clinical practice, are often the therapeutic solution in difficult cases. Advances made in recent years bring up the question of knowing whether or not logic is near to replacing empiricism.

Anti-Arrhythmia Agents↗