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At least 253 records · Page 14Linked to original sources
PubMed2005

Logical analysis of diffuse large B-cell lymphomas.

OBJECTIVE: The goal of this study is to re-examine the oligonucleotide microarray dataset of Shipp et al., which contains the intensity levels of 6817 genes of 58 patients with diffuse large B-cell lymphoma (DLBCL) and 19 with follicular lymphoma (FL), by means of the combinatorics, optimisation, and logic-based methodology of logical analysis of data (LAD). The motivations for this new analysis included the previously demonstrated capabilities of LAD and its expected potential (1) to identify different informative genes than those discovered by conventional statistical methods, (2) to identify combinations of gene expression levels capable of characterizing different types of lymphoma, and (3) to assemble collections of such combinations that if considered jointly are capable of accurately distinguishing different types of lymphoma. METHODS AND MATERIALS: The central concept of LAD is a pattern or combinatorial biomarker, a concept that resembles a rule as used in decision tree methods. LAD is able to exhaustively generate the collection of all those patterns which satisfy certain quality constraints, through a systematic combinatorial process guided by clear optimization criteria. Then, based on a set covering approach, LAD aggregates the collection of patterns into classification models. In addition, LAD is able to use the information provided by large collections of patterns in order to extract subsets of variables, which collectively are able to distinguish between different types of disease. RESULTS: For the differential diagnosis of DLBCL versus FL, a model based on eight significant genes is constructed and shown to have a sensitivity of 94.7% and a specificity of 100% on the test set. For the prognosis of good versus poor outcome among the DLBCL patients, a model is constructed on another set consisting also of eight significant genes, and shown to have a sensitivity of 87.5% and a specificity of 90% on the test set. The genes selected by LAD also work well as a basis for other kinds of statistical analysis, indicating their robustness. CONCLUSION: These two models exhibit accuracies that compare favorably to those in the original study. In addition, the current study also provides a ranking by importance of the genes in the selected significant subsets as well as a library of dozens of combinatorial biomarkers (i.e. pairs or triplets of genes) that can serve as a source of mathematically generated, statistically significant research hypotheses in need of biological explanation.

Combinatorial Chemistry Techniques↗
PubMed2004

Referential cohesion and logical coherence of narration after closed head injury.

A group with closed head injury was compared to neurologically intact controls regarding the referential cohesion and logical coherence of narrative production. A sample of six stories was obtained with tasks of cartoon-elicited story-telling and auditory-oral retelling. We found deficits in the clinical group with respect to referential cohesion, logical coherence, and accuracy of narration. The occurrence of deficits depended on the condition of narrative production and, to some extent, on the particular story used. The primary implications of this study pertain to the attention given by researchers to the feature of discourse production being studied and processing demands of the task.

Adult↗
PubMed2006

Interlinking physical beliefs: children's bias towards logical congruence.

Young children's naïve beliefs about physics are commonly studied as isolated pieces of knowledge. The current paper takes a different approach. It asks whether preschoolers interlink individual beliefs into larger configurations or Gestalts. Such Gestalts bring together knowledge such as how an object's mass relates to its sinking speed, how an object's volume relates to its sinking speed, and how mass and volume are correlated. The particular form of organization explored here is referred to as logical congruence, the logical correspondence in directions among three physical relations. Are children's guesses about one physical relation congruent with their beliefs about the other two relations? And can they learn a congruent set of relations more readily than an incongruent set? Two different physical domains were explored, one in which children commonly hold pre-existing beliefs, and one in which they are likely to lack such beliefs. The results in both domains show a strong bias towards congruent knowledge configurations in young children. These findings may explain children's difficulties learning inherently incongruous concepts such as density.

Bias↗
PubMed2006

Comparison of neurofuzzy logic and neural networks in modelling experimental data of an immediate release tablet formulation.

This study compares the performance of neurofuzzy logic and neural networks using two software packages (INForm and FormRules) in generating predictive models for a published database for an immediate release tablet formulation. Both approaches were successful in developing good predictive models for tablet tensile strength and drug dissolution profiles. While neural networks demonstrated a slightly superior capability in predicting unseen data, neurofuzzy logic had the added advantage of generating rule sets representing the cause-effect relationships contained in the experimental data.

Fuzzy Logic↗
PubMed2006

Application of fuzzy-logic models for metabolic control analysis.

A priori information or valuable qualitative knowledge can be incorporated explicitly to describe enzyme kinetics making use of fuzzy-logic models. Although restricted to linear relationships, it is shown that fuzzy-logic augmented models are not only able to capture non-linear features of enzyme kinetics but also allow the proper mathematical treatment of metabolic control analysis. The explicit incorporation of valuable qualitative knowledge is crucial, particularly when handling data estimated from in vivo kinetics studies, since this experimental information is scarce and usually contains measurement errors. Therefore, data-driven techniques, such as the one presented in this work, form a serious alternative to established kinetics approaches.

Animals↗
PubMed2006

A new approach to diabetic control: fuzzy logic and insulin pump technology.

Diabetes is a major health problem. Since the utilisation of insulin in the 1920s there have been myriad problems in developing suitable technologies to formulate and administer correct dosages to temper this metabolic disease. From multiple daily injections, nasal inhalations and enzymatic supplementation these artificial shortcuts still do not have the ability to fully replicate a 'normoglycaemic' state of being. In this paper, we sought to explore the use of insulin pumps and the application of fuzzy logic technology to act as an 'artificial pancreas' in diabetic patients. This paper builds on our previous work [Grant P, Naesh, O. Fuzzy logic and decision-making in anaesthetics. J Roy Soc Med 2005;98(1):7-9 [review]].

Biotechnology↗
PubMed2006

Popperian epidemiology and the logic of bi-conditional modus tollens arguments for refutational analysis of randomised controlled trials.

Popperian epidemiology is a biomedical science tool based on the hypothesis-deductive method and the falsifiability of scientific hypotheses. This article explores the applicability of the refutationist logic tools in the analysis of a randomised controlled trial (RCT), the randomised Aldactone evaluation study (RALES). This was carried out by using bi-conditional modus-tollens arguments of the type (i) P-then-Q(n) and (ii) Q(n)-If-X(P), X(P) being a set of potential falsifiers of Q(n) as part of the explicit falsity-content of P. In this model, P is the main hypothesis and Q(n) one or more logical predictions to be tested. The X(P) argument represents inclusion criteria, exclusion criteria and conditional criteria of the RCT so every P-then-X(P) argument should be fulfilled in canonical form to corroborate P-then-Q(n). Thus, falsifiability of a RCT would be determined by the empirical content of the conditional argument Q(n)-If-X(P) and its external validity would be determined by the empirical content of X(P). In this way it would be possible to mathematically assess the external validity of a RCT if the observational predicates of the X(P) argument in a given population are known. According to this popperian model, applicability of the RCT results to clinical practice implies transferring of all its empirical content, in other words, the totality of its truth and falsity contents. Thus, to ignore the explicit falsity-content of a RCT such as RALES may jeopardise its potential benefits in clinical practice as suggested by recent studies.

Clinical Trials as Topic↗
PubMed2006

HPV infection in relation to OSCC histological grading and TNM stage. Evaluation by traditional statistics and fuzzy logic model.

We aimed to evaluate if in oral squamous cell carcinoma (OSCC) there is a relationship between histological grading (HG), TNM clinical stage and HPV infection; and to study the performance of fuzzy logic compared to traditional statistics, in the analysis of HPV status and correlates of OSCC. In cross-sectional analysis, the study group comprised 63 patients (mean age 68.89 years (SD +/-11.78), range (32-93); males 28 (44.4%), females 35 (55.6%)) with OSCC histologically diagnosed. HPV-DNA was studied in exfoliated oral epithelial cells by nested PCR (MY09/MY11 and GP5+/GP6+ primers). Data were analysed in parallel by traditional statistics with multivariate analysis and a fuzzy logic (FL) technique (membership functions as input, the ANFIS methodology, and the Sugeno's model of first order). HPV infection was detected in 24/63 (38.1%) of OSCC, as being HPV+ve 14/36 (38.9%) in G1, 7/18 (38.9%) in G2, and 3/9 (33.3%) in G3; HPV+ve 8/33 (24.2%) in Stage I, 9/12 (75.0%) in Stage II, 6/11(54.5%) in Stage III, and 1/7 (14.3%) in Stage IV. In both methods of analysis, no significantly increased risk of HPV infection was found for any HG score; whereas, TNM stage II was significantly associated to HPV infection (p=0.004; OR=9.375 (95% CI=2.030:43.30); OR'=11.148 (95% CI=1.951:43.30)), and, in particular, to primary tumour size T2 (p=0.0036; OR=7.812 (95% CI=1.914:31.890); OR'=9.414 (95% CI=1.846:48.013)); FL (% of prevision: 79.8; Root Mean-Square Error (RMSE): 0.29). No association was found between HPV infection and any demographical variable. Our findings show an association between HPV infection with TNM (stage II-T2), but not with histological grading of OSCC. Also, FL seems to be an additional effective tool in analysing the relationship of HPV infection with correlates of OSCC.

Adult↗
PubMed1997

Using fuzzy logic to predict response to citalopram in alcohol dependence.

INTRODUCTION: The prediction of patient response to new pharmacotherapies for alcohol dependence has usually not been successful with standard statistical techniques. We hypothesized that fuzzy logic, a qualitative computational approach, could predict response to 40 mg/day citalopram and 40 mg/day citalopram with a brief psychosocial intervention in alcohol-dependent patients. METHODS: Two data sets were formed with patients from our studies who received 40 mg/day citalopram alone (n = 34) or 40 mg/day citalopram and a brief psychosocial intervention (n = 28). The output variable, "response," was the percentage decrease in alcohol intake from baseline. Input variables included age, gender, baseline alcohol intake, and levels of anxiety, depression, alcohol dependence, and alcohol-related problems. RESULTS: A fuzzy rulebase was created from the data of 26 randomly chosen patients who received 40 mg/day citalopram and was used to predict the responses of the remaining eight patients. Eight rules related response with depression, anxiety, alcohol dependence, alcohol-related problems, age, and baseline alcohol intake. The average magnitude of the error in the predictions (RMSE) was 2.6 with a bias (ME) of 0.6. Predicted and actual response correlated (r = 0.99; p < 0.001). A fuzzy rulebase was created from the data of 28 randomly chosen patients who received 40 mg/day citalopram and a brief psychosocial intervention and was used to predict the responses of the remaining five patients. Six rules related response with age, anxiety, depression, alcohol dependence, and baseline alcohol intake with good predictive performance (RMSE = 6.4; ME = -1.5; r = 0.96; p < 0.01). CONCLUSIONS: This study indicates that fuzzy logic modeling can predict response to pharmacotherapies for alcohol dependence.

Alcoholism↗
PubMed2002

A fuzzy-logic antiswing controller for three-dimensional overhead cranes.

In this paper, a new fuzzy antiswing control scheme is proposed for a three-dimensional overhead crane. The proposed control consists of a position servo control and a fuzzy-logic control. The position servo control is used to control crane position and rope length, and the fuzzy-logic control is used to suppress load swing. The proposed control guarantees not only prompt suppression of load swing but also accurate control of crane position and rope length for simultaneous travel, traverse, and hoisting motions of the crane. Furthermore, the proposed control provides practical gain tuning criteria for easy application. The effectiveness of the proposed control is shown by experiments with a three-dimensional prototype overhead crane.

Computer Simulation↗
PubMed1995

A fuzzy logic diagnosis system for classification of pharyngeal dysphagia.

Identification and classification of the dysphagic patient at risk of aspiration is important from a clinical point of view. Recently, we have developed techniques to quantify various biomechanical parameters that characterize the dysphagic patient, and have developed an expert system to classify patients based on these measurements. The purpose of the present investigation was to develop a fuzzy logic diagnosis system for classification of the patient with pharyngeal dysphagia into four categories of risk for aspiration. Non-invasive acceleration and swallow pressure measurements were obtained and five parameters were extracted from these measurements. A set of membership functions were defined for each parameter. The measured parameter values were fuzzified and fed to a rule base which provided a set of output membership values corresponding to each of the categories. The set of output values were defuzzified to obtain a continuous measure of classification. The fuzzy system was evaluated using the data obtained from 22 subjects. There was a complete agreement between the fuzzy system classification and the clinician's classification in 18 of the 22 patients. The fuzzy system overestimated the risk by half a category in two patients and underestimated by half a category in two patients. The fuzzy logic diagnosis system, together with the biomechanical measures, provides a tool for continued patient assessment on a daily basis to identify the patient who needs further videofluorography examination.

Biomechanical Phenomena↗
PubMed2002

State detection and control of overloads in the anaerobic wastewater treatment using fuzzy logic.

The two-stage anaerobic wastewater pre-treatment was modelled and controlled. The biological state of the reactors could be predicted using a fuzzy logic system and based upon this, proper control actions were taken automatically in order to avoid an overload. The system was designed to handle very strong fluctuations in the concentration of the substrate and the volumetric loading rate. Hydrogen concentration together with methane concentration, gas production rate. pH and the filling level of the acidification buffer tank were used as input variables for the fuzzy logic system. The manipulated variables were the flow rate from the acidification buffer tank into the methane reactor, the temperature and pH of both reactors, the circulation rate of the fixed bed reactor, back flow from the methane reactor into the acidification, and the control of the feed into the acidification buffer tank. The developed control system was successfully tested on a fully automated lab scale two-stage anaerobic digester. Different types of wastewater from food processing industries were successfully applied. Even a restart of feeding with very high COD concentrations (100 gl(-1) after several days of stand by was handled successfully. Effluent concentrations could be kept low without using TOC, COD or equivalent measurements.

Bacteria, Anaerobic↗
PubMed2000

A logic for biological systems.

This paper proposes a specification language, hybrid projection temporal logic of modelling, analyzing and verifying biological systems which can be considered, in general, to be hybrid systems consisting of a non-trivial mixture of discrete and continuous components. The syntax and semantics of the logic are presented, and some examples of hybrid systems are modelled to illustrate the formalism.

Antigen-Antibody Reactions↗
PubMed1997

Fuzzy logic in computer-aided breast cancer diagnosis: analysis of lobulation.

This paper illustrates how a fuzzy logic approach can be used to formalize terms in the American College of Radiology (ACR) Breast Imaging Lexicon. In current practice, radiologists make a relatively subjective determination for many terms from the lexicon related to breast cancer diagnosis. Lobulation and microlobulation of nodules are two important features in the ACR lexicon. We offer an approach for formalizing the distinction of these features and also formalize the description of intermediate cases between lobulated and microlobulated masses. In this paper it is shown that fuzzy logic can be an effective tool in dealing with this kind of problem. The proposed formalization creates a basis for the next three steps (i) extended verification with blinded comparison studies. (ii) the automatic extraction of the related primitives from the image, and (iii) the detection of lobulated and microlobulated masses based on these primitives.

Breast Neoplasms↗
PubMed1997

Fuzzy logic for model adaptation of a pharmacokinetic-based closed loop delivery system for pancuronium.

In this paper, we investigate the ability of fuzzy to adapt the parameters of a pharmacokinetic and pharmacodynamic model-based controller for the delivery of the muscle relaxant pancuronium. The system uses the model to control the rate of drug delivery and uses feedback from a sensor which measures muscle relaxation level to adapt the model using fuzzy logic. The control strategy administers mini-bolus doses of pancuronium and modulates the magnitude and time interval between the bolus doses to maintain a patient's muscle relaxation within an allowable range specified by the user. Before each new dose is given, the fuzzy logic adaptation scheme uses the error between the predicted patient response and the measured response to adapt the model. The system was tested using computer simulation by varying the parameters of the model by 50% from their nominal values. It was also evaluated in a clinical trial of five patients undergoing surgical procedures lasting 5 h or longer.

Adult↗
PubMed2001

Fuzzy logic and its applications in medicine.

Fuzzy set theory and fuzzy logic are a highly suitable and applicable basis for developing knowledge-based systems in medicine for tasks such as the interpretation of sets of medical findings, syndrome differentiation in Eastern medicine, diagnosis of diseases in Western medicine, mixed diagnosis of integrated Western and Eastern medicine, the optimal selection of medical treatments integrating Western and Eastern medicine, and for real-time monitoring of patient data. This was verified by trials with the following systems that were developed by our group in Vietnam: a fuzzy Expert System for Syndromes Differentiation in Oriental Traditional Medicine, an Expert System for Lung Diseases using fuzzy logic, Case Based Reasoning for Medical Diagnosis using fuzzy set theory, a diagnostic system combining disease diagnosis of Western Medicine with syndrome differentiation of Oriental Traditional Medicine, a fuzzy system for classification of Western and Eastern medicaments and finally, a fuzzy system for diagnosis and treatment of integrated Western and Eastern Medicine.

Diagnosis, Differential↗
PubMed2002

LoMAPAM--Logical Model of Autowave Processes of Amoebic Movement.

This work describes a logical discrete model of the spatiotemporal dynamics of amoebic movement (Logical Model of Autowave Processes of Amoebic Movement (LoMAPAM)) based on finite automata (homogeneous structures) and specified for Physarum polycephalum. The basic system of passing rules for the information and regulation levels of the model, describing the contractile behavior of the ectoplasmic walls of P. polycephalum, enables a rhythmic generation of contractile waves and their propagation in the ectoplasmic wall due to the created structure of the LoMAPAM model. The finite automata corresponds to elementary square planar elements. This construction is alike homogeneous structures with the only exception is its finite. The planar element is assigned to the pair of integers (i,j). The state vector defined for every element (i,j) in discrete time t will have three components. Each of them will be written in one of the matrices B, C, or W. The information matrix B describes the state of the matter. The regulation matrix C, the local Ca(2+) concentration. The flow matrix W describes the local flow of endoplasm or ectoplasm. The passing rules for the state vector was written in the form of Boolean functions. Six actomyosin generators placed on a circle and three and five neighbouring ectoplasmatic generators on a line and a layer of endoplasm were analysed.

Animals↗
PubMedDate not supplied

Development of a program logic model to measure the processes and outcomes of a nurse-managed community health clinic.

Evaluation is an essential process that permits assessing the effectiveness and efficiency of planned programs. In implementing a new nurse-managed Community Health Clinic targeting services for the homeless and underserved, the stakeholders considered an evaluation process integral to the planning stage of the clinic as a whole as well as of all the different programs being offered. The program logic model was chosen and modified to guide evaluation. Work to develop the evaluation model and its components began before the clinic opened. This article describes the development of the modified program logic model, how it was modified, and the rationale for its modifications. We highlight the process of developing the evaluation model because we found limited descriptions of the process in the literature. The evaluation process itself will be evaluated on an ongoing basis to determine if it is capturing the evaluation needs of the clinic project accurately.

Community Health Services↗