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PubMed2006

A new hybrid method based on fuzzy-artificial immune system and k-nn algorithm for breast cancer diagnosis.

The use of machine learning tools in medical diagnosis is increasing gradually. This is mainly because the effectiveness of classification and recognition systems has improved in a great deal to help medical experts in diagnosing diseases. Such a disease is breast cancer, which is a very common type of cancer among woman. As the incidence of this disease has increased significantly in the recent years, machine learning applications to this problem have also took a great attention as well as medical consideration. This study aims at diagnosing breast cancer with a new hybrid machine learning method. By hybridizing a fuzzy-artificial immune system with k-nearest neighbour algorithm, a method was obtained to solve this diagnosis problem via classifying Wisconsin Breast Cancer Dataset (WBCD). This data set is a very commonly used data set in the literature relating the use of classification systems for breast cancer diagnosis and it was used in this study to compare the classification performance of our proposed method with regard to other studies. We obtained a classification accuracy of 99.14%, which is the highest one reached so far. The classification accuracy was obtained via 10-fold cross validation. This result is for WBCD but it states that this method can be used confidently for other breast cancer diagnosis problems, too.

Algorithms↗
PubMed1997

Exchanging clinical knowledge via Internet.

The need for effective and efficient exchange of clinical knowledge is increasing. Paper based methods for managing clinical knowledge are not meeting the demand for knowledge and this has undoubtedly contributed to the widely reported failures of clinical guidelines. Internet affords both opportunities and dangers for clinical knowledge. Systems such as Wax have demonstrated the importance of intuitive structure in the management of knowledge. We report on a new initiative for the global management of clinical knowledge.

Artificial Intelligence↗
PubMed1999

Specific cognitive deficits in mild frontal variant frontotemporal dementia.

Eight patients with relatively mild frontal variant frontotemporal dementia (fvFTD) were compared with age- and IQ-matched control volunteers on tests of executive and mnemonic function. Tests of pattern and spatial recognition memory, spatial span, spatial working memory, planning, visual discrimination learning/attentional set-shifting and decision-making were employed. Patients with fvFTD were found to have deficits in the visual discrimination learning paradigm specific to the reversal stages. Furthermore, in the decision-making paradigm, patients were found to show genuine risk-taking behaviour with increased deliberation times rather than merely impulsive behaviour. It was especially notable that these patients demonstrated virtually no deficits in other tests that have also been shown to be sensitive to frontal lobe dysfunction, such as the spatial working memory and planning tasks. These results are discussed in relation to the possible underlying neuropathology, the anatomical connectivity and the hypothesized heterogeneous functions of areas of the prefrontal cortex. In particular, given the nature of the cognitive deficits demonstrated by these patients, we postulate that, relatively early in the course of the disease, the ventromedial (or orbitofrontal) cortex is a major locus of dysfunction and that this may relate to the behavioural presentation of these patients clinically described in the individual case histories.

Adult↗
PubMed2006

Analysis of a master-slave architecture for distributed evolutionary computations.

This paper introduces a new mathematical model of the master-slave architecture for distributed evolutionary computations (EC). This model is validated using a concrete implementation based on the Distributed BEAGLE C++ framework. Results show that contrary to (current) popular belief, master-slave architectures are able to scale well over local area networks of workstations using off-the-shelf networking equipment. The main properties of the master-slave are also compared with those of the more mainstream island-model.

Artificial Intelligence↗
PubMed2003

Behavioral impulsivity paradigms: a comparison in hospitalized adolescents with disruptive behavior disorders.

BACKGROUND: Behavioral impulsivity paradigms vary widely and studies using these measures have typically relied on a single measure used in isolation. As a result, comparisons between measures are difficult, with little consensus regarding which method may be most sensitive to individual impulsivity differences of different populations. METHOD: A single testing session of each of four different impulsivity tasks was completed by two groups of adolescents aged 13-17: hospitalized inpatients with disruptive behavior disorders (DBD; n = 22) and controls (n = 22). Tasks included two rapid-decision (IMT/DMT and GoStop) and two reward-directed (TC and SKIP) impulsivity paradigms. Behavioral testing took place within 3 days of hospitalization for the adolescents with DBD. RESULTS: Compared to controls, the DBD group exhibited higher commission error rates, lower inhibited response rates after a stop-signal, and twice as many reward-directed responses even after IQ differences between the groups were taken into account. When the four paradigms were compared, effect-size calculations indicated that the two rapid-decision paradigms were more sensitive to group differences than the reward-directed tasks. CONCLUSIONS: Despite the initiation of pharmacotherapy within the first 3 days of hospitalization, in contrast to the control group, the adolescents with DBD performed consistently with what has been operationally defined as impulsivity. Based on these results, these tasks appear to measure similar, but unique components of the impulsivity construct. With further study, laboratory behavioral paradigms may prove to be useful additions to current clinical diagnostic and treatment procedures in a variety of psychiatric populations.

Adolescent↗
PubMed2005

Inferences of competence from faces predict election outcomes.

We show that inferences of competence based solely on facial appearance predicted the outcomes of U.S. congressional elections better than chance (e.g., 68.8% of the Senate races in 2004) and also were linearly related to the margin of victory. These inferences were specific to competence and occurred within a 1-second exposure to the faces of the candidates. The findings suggest that rapid, unreflective trait inferences can contribute to voting choices, which are widely assumed to be based primarily on rational and deliberative considerations.

Aging↗
PubMed2006

Evaluation of PROforma as a language for implementing medical guidelines in a practical context.

BACKGROUND: PROforma is one of several languages that allow clinical guidelines to be expressed in a computer-interpretable manner. How these languages should be compared, and what requirements they should meet, are questions that are being actively addressed by a community of interested researchers. METHODS: We have developed a system to allow hypertensive patients to be monitored and assessed without visiting their GPs (except in the most urgent cases). Blood pressure measurements are performed at the patients' pharmacies and a web-based system, created using PROforma, makes recommendations for continued monitoring, and/or changes in medication. The recommendations and measurements are transmitted electronically to a practitioner with authority to issue and change prescriptions. We evaluated the use of PROforma during the knowledge acquisition, analysis, design and implementation of this system. The analysis focuses on the logical adequacy, heuristic power, notational convenience, and explanation support provided by the PROforma language. RESULTS: PROforma proved adequate as a language for the implementation of the clinical reasoning required by this project. However a lack of notational convenience led us to use UML activity diagrams, rather than PROforma process descriptions, to create the models that were used during the knowledge acquisition and analysis phases of the project. These UML diagrams were translated into PROforma during the implementation of the project. CONCLUSION: The experience accumulated during this study highlighted the importance of structure preserving design, that is to say that the models used in the design and implementation of a knowledge-based system should be structurally similar to those created during knowledge acquisition and analysis. Ideally the same language should be used for all of these models. This means that great importance has to be attached to the notational convenience of these languages, by which we mean the ease with which they can be read, written, and understood by human beings. The importance of notational convenience arises from the fact that a language used during knowledge acquisition and analysis must be intelligible to the potential users of a system, and to the domain experts who provide the knowledge that will be used in its construction.

Antihypertensive Agents↗
PubMed2004

Intrusion detection using rough set classification.

Recently machine learning-based intrusion detection approaches have been subjected to extensive researches because they can detect both misuse and anomaly. In this paper, rough set classification (RSC), a modern learning algorithm, is used to rank the features extracted for detecting intrusions and generate intrusion detection models. Feature ranking is a very critical step when building the model. RSC performs feature ranking before generating rules, and converts the feature ranking to minimal hitting set problem addressed by using genetic algorithm (GA). This is done in classical approaches using Support Vector Machine (SVM) by executing many iterations, each of which removes one useless feature. Compared with those methods, our method can avoid many iterations. In addition, a hybrid genetic algorithm is proposed to increase the convergence speed and decrease the training time of RSC. The models generated by RSC take the form of "IF-THEN" rules, which have the advantage of explication. Tests and comparison of RSC with SVM on DARPA benchmark data showed that for Probe and DoS attacks both RSC and SVM yielded highly accurate results (greater than 99% accuracy on testing set).

Algorithms↗
PubMed2002

[Development of grade level norms for reading speed and writing errors of Turkish elementary school children].

INTRODUCTION: Despite being in the normal intelligence range, children with learning disorders fail to reach expected academic performance levels. Clinical diagnosis and decisions for therapeutic management for these children require the use of academic achievement tests. The lack of reliable achievement tests and age appropriate reading speed and writing norms hinder clinical studies with Turkish children. OBJECTIVE: To develop and establish Turkish norms of an assessment tool which will aid in the objective evaluation and diagnosis of learning disorders. METHOD: A total of 2572 children attending the 1st-5th grades of randomly selected elementary schools belonging to different socioeconomic levels constituted the sample of the study. The number of words read from grade-level appropriate scripts in 1 minute indicated reading speed. A three-sentence script containing repeating consonants p-b-t-d-m-n-v-f was dictated to determine writing errors. RESULTS AND DISCUSSION: Grade levels of reading speed increase and writing errors decrease as the child grows. Mean, standard deviation and standard error scores indicate that objective academic achievement criteria were reached. Achievement differences according to gender and sociocultural status, which were not the subject of this study, also seem to be important variables.

English Abstract↗
PubMed1992

[Contribution of expert systems in clinical practice: apropos of the Penelope experience, an expert system in assisted diagnosis and therapy of ovarian adenocarcinoma].

An expert system (ES) for Diagnosis and Therapy of ovarian adenocarcinoma has been developed at the Institut Gustave-Roussy. From surgical and histological results, clinical examination and additional investigative reports, the system presents a synthesis and then determines the stage of the disease. The system than proposes therapeutic indications adapted to the characteristics of the illness and of the patient, and edits a report at the end of the ES consultation. This experience allowed us to specify the field of ES applications in oncology. As tools for diagnosis and therapy, they cannot act as a substitute for the know-how of the physician, as too many medical decisions remain difficult to formalize in the ES. On the other hand the use of artificial intelligence techniques appears to be useful for establishing coherent data bases, which are necessary pre-requisites for clinical research in oncology. The integration of the system in the Hospital Information System is the guarantee of its use in current clinical practice.

Adenocarcinoma↗
PubMed1992

A study of the cognitive aspects of sexual decision making in adolescent females.

A comprehensive sexuality questionnaire was administered to 37 females, ages 13 through 16 years, who attended clinics for routine health care. Subjects completed standardized scales of self-concept, locus of control, and future orientation. They also were given a short battery of standardized cognitive tests. Three groups were identified: Group 1 was sexually active and using contraception reliably, Group 2 was not using contraception reliably, and Group 3 had not been sexually active. Group 1 adolescents had higher scores on the vocabulary subtest of the WISC-R (F = 3.4, p less than .05) than did Group 2 adolescents, over and above the effect of socioeconomic status (SES). Group 1 subjects had higher scores on knowledge of sex and contraception than did Group 2 (F = 3.3, p less than .05). Group 1 had more internal locus of control (F = 7.0, p less than .005) than did Group 2 over and above the effect of SES. Mean scores for Group 3 adolescents were intermediate and not significantly different. The findings suggest that cognitive factors may influence contraceptive behavior in adolescent females.

Adolescent↗
PubMed1984

The elderly patient and informed consent. Empirical findings.

Informed consent with the elderly patient and the competency of this patient population have been neglected issues in medicine and law. Particularly, the competency of the elderly patient has received little empirical investigation. The present study examines the capacity of geriatric patients to consent to research participation. Competency is investigated through the use of hypothetical consent information on three dimensions: comprehension of consent material, quality of reasoning about the decision to participate or not participate in research, and reasonable choice regarding participation. The results indicate that elderly patients' choices about those projects in which participation is "reasonable" do not differ, by and large, from younger patients. However, the elderly show significantly poorer comprehension of consent information. Thus, screening for competency and providing special instructions may become an important part of the research process when the elderly are participants.

Adult↗
PubMed1996

Distributed intelligent data analysis in diabetic patient management.

This paper outlines the methodologies that can be used to perform an intelligent analysis of diabetic patients' data, realized in a distributed management context. We present a decision-support system architecture based on two modules, a Patient Unit and a Medical Unit, connected by telecommunication services. We stress the necessity to resort to temporal abstraction techniques, combined with time series analysis, in order to provide useful advice to patients; finally, we outline how data analysis and interpretation can be cooperatively performed by the two modules.

Computer Communication Networks↗
PubMed1977

Delay of gratification: decisional self-control and experience with delay intervals.

Actual and verbally reported decisional self-control choices (e.g., 1 penny now or 2 pennies in 1 minute) were obtained from 40 retarded adolescents who participated in a sheltered workshop. Prior to each of their eight choices, one-half of the students experienced the same time interval that was included in the choice for that day (e.g., 1 minute). Analysis of the number of actual and reported delay choices yielded a significant effect for experience, with the treatment group making more delay choices. In addition to suggesting that decisional self-control can be facilitated by prior exposure to delay intervals, the results indicated that verbally reported choices can be used as a reliable and valid indication of actual choices.

Adolescent↗