A global optimisation approach to classification in medical diagnosis and prognosis
- Authors: Bagirov, Adil , Rubinov, Alex , Yearwood, John , Stranieri, Andrew
- Date: 2001
- Type: Text , Conference paper
- Relation: Paper presented at 34th Hawaii International Conference on System Sciences, HICSS-34, Maui, Hawaii, USA : 3rd-6th January 2001
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- Description: In this paper global optimisation-based techniques are studied in order to increase the accuracy of medical diagnosis and prognosis with FNA image data from the Wisconsin Diagnostic and Prognostic Breast Cancer databases. First we discuss the problem of determining the most informative features for the classification of cancerous cases in the databases under consideration. Then we apply a technique based on convex and global optimisation to breast cancer diagnosis. It allows the classification of benign cases and malignant ones and the subsequent diagnosis of patients with very high accuracy. The third application of this technique is a method that calculates centres of clusters to predict when breast cancer is likely to recur in patients for which cancer has been removed. The technique achieves higher accuracy with these databases than reported elsewhere in the literature.
- Description: 2003003950
An argumentation-based multi-agent system for e-tourism dialogue
- Authors: Avery, John , Yearwood, John , Stranieri, Andrew
- Date: 2001
- Type: Text , Conference paper
- Relation: Paper presented at Hybrid Information Systems, First International Workshop on Hybrid Intelligent Systems, Adelaide : 11th - 12th December, 2003 p. 497-512
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000112
Argumentation structures that integrate dialectical and non-dialectical reasoning
- Authors: Stranieri, Andrew , Zeleznikow, John , Yearwood, John
- Date: 2001
- Type: Text , Journal article
- Relation: Knowledge Engineering Review Vol. 16, no. 4 (Dec 2001), p. 331-348
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- Reviewed:
- Description: Argumentation concepts have been applied to numerous knowledge engineering endeavours in recent years. For example, a variety of logics have been developed to represent argumentation in the context of a dialectical situation such as a dialogue. In contrast to the dialectical approach, argumentation has also been used to structure knowledge. This can be seen as a non-dialectical approach. The Toulmin argument structure has often been used to structure knowledge non-dialectically yet most studies that apply the Toulmin structure do not use the original structure but vary one or more components. Variations to the Toulmin structure can be understood as different ways to integrate a dialectical perspective with a non-dialectical one. Drawing the dialectical/non-dialectical distinction enables the specification of a framework called the generic actual argument model that is expressly non-dialectical. The framework enables the development of knowledge-based systems that integrate a variety of inference procedures, combine information retrieval with reasoning and facilitate automated document drafting. Furthermore, the non-dialectical framework provides the foundation for simple dialectical models. Systems based on our approach have been developed in family law, refugee law, determining eligibility for government legal aid, copyright law and e-tourism.
- Description: C1
- Description: 2003002516
System development a la MODDE
- Authors: Meikle, Tunde , Yearwood, John
- Date: 2001
- Type: Text , Conference paper
- Relation: Paper presented at 8th International Conference on Artificial Intelligence and Law - ICAIL '01, St. Louis, Missouri, USA : 21st-25th May 2001 p. 99-103
- Full Text: false
- Description: This paper describes the MODDE (Model of Decision support system Design and Evaluation) framework in some detail. The work is in progress and is being currently applied to the EMBRACE project being developed for the Refugee Review Tribunal (RRT) of Australia. Refugee law is the general legal area we are working in, while the specific domain under investigation is that of the decision makers at the RRT. EMBRACE is a decision support system being designed to assist the RRT in maintaining consistency of decisions, and preserve discretion of decision makers as well as making it easier to cope with high volumes of work in decreasing time frames. The use of the MODDE framework is intended to facilitate systematic attention to important features of decision making in our specific legal domain and to provide a sound basis upon which to evaluate a part of the system intrinsic to user acceptance. Copyright 2001 ACM.
- Description: 2003003947
Tools for placing legal decision support systems on the world wide web
- Authors: Stranieri, Andrew , Yearwood, John , Zeleznikow, John
- Date: 2001
- Type: Text , Conference paper
- Relation: Paper presented at Eighth International Conference on Artificial Intelligence and Law, ICAIL 2001, St. Louis, USA : 21st-25th May 2001
- Full Text: false
- Description: 2003003944
Using global optimization to improve classification for medical diagnosis and prognosis
- Authors: Bagirov, Adil , Rubinov, Alex , Yearwood, John
- Date: 2001
- Type: Text , Journal article
- Relation: Topics in health information management Vol. 22, no. 1 (2001), p. 65-74
- Full Text: false
- Description: Global optimization-based techniques are studied in order to increase the accuracy of medical diagnosis and prognosis with data from various databases. First, we discuss feature selection, the problem of determining the most informative features for classification in the databases under consideration. Then, we apply a technique based on convex and global optimization for classification in these databases. The third application of this technique is a method that calculates centers of clusters to predict when breast cancer is likely to recur in patients for which cancer has been removed. The technique achieves high accuracy with these databases. Better classifiers will lead to improved assistance in making medical diagnostic and prognostic decisions.
- Description: 2003003662
A global optimization approach to classification
- Authors: Bagirov, Adil , Rubinov, Alex , Yearwood, John
- Date: 2002
- Type: Text , Journal article
- Relation: Optimization and Engineering Vol. 9, no. 7 (2002), p. 129-155
- Full Text: false
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- Description: In this paper is presented an hybrid algorithm for finding the absolute extreme point of a multimodal scalar function of many variables. The algorithm is suitable when the objective function is expensive to compute, the computation can be affected by noise and/or partial derivatives cannot be calculated. The method used is a genetic modification of a previous algorithm based on the Prices method. All information about behavior of objective function collected on previous iterates are used to chose new evaluation points. The genetic part of the algorithm is very effective to escape from local attractors of the algorithm and assures convergence in probability to the global optimum. The proposed algorithm has been tested on a large set of multimodal test problems outperforming both the modified Prices algorithm and classical genetic approach.
- Description: C1
- Description: 2003000061
An argumentation shell for supporting the development and drafting of legal arguments
- Authors: Yearwood, John , Stranieri, Andrew
- Date: 2002
- Type: Text , Journal article
- Relation: Information and Communication Technology Law Vol. 11, no. 1 (2002), p. 75-86
- Full Text: false
- Reviewed:
- Description: This article describes an argumentation shell to support the formulation, representation and drafting of legal arguments. The shell can be used to capture generic arguments in many legal domains as well as to assist decision-makers in constructing their own actual arguments . The shell demonstrates that knowledge represented using the generic/actual argument model (GAAM) (a variant of Toulmin's argument structure) can be used to: (a) support the development of complex arguments, (b) add context and increase specificity for the retrieval of relevant documents, (c) incorporate background knowledge, (d) assist in the drafting of documents that represent arguments made, and (e) provide a structure for complex inferences requiring a range of mechanisms. The shell can be used to support decision making in a range of legal domains, including discretionary domains.
- Description: C1
- Description: 2003000141
An introduction algorithm with selection significance based on a fuzzy deriviative
- Authors: Mammadov, Musa , Yearwood, John
- Date: 2002
- Type: Text , Conference paper
- Relation: Paper presented at Hybrid Information Systems (Advances in Soft Computing), Adelaide : 11th December, 2001
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000076
Discovering interesting association rules from legal databases
- Authors: Ivkovic, Sasha , Yearwood, John , Stranieri, Andrew
- Date: 2002
- Type: Text , Journal article
- Relation: Information & Communication Technology Law Vol. 11, no. 1 (2002), p. 35-47
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- Reviewed:
- Description: The Knowledge Discovery from Databases (KDD) technique called 'association rules' is applied to a large data set representing applicants for government-funded legal aid. Results indicate that KDD can be an invaluable tool for legal analysts. Association rules discovered identify associations between variables that are present in the data set though are not necessarily causal. Interesting rules can prompt analysts to formulate hypotheses for further investigation. The identification of interesting rules is typically performed using an objective measure of 'interesting' although this measure is often not sufficiently accurate to eliminate all uninteresting rules. In this article, a subjective measure of interestingness is adopted in conjunction with the objective measures. This leads to the ability to focus more accurately on those rules that surprise the analyst and are therefore more likely to be interesting. In general, KDD techniques have not been applied to law despite possible benefits because data is often stored in narrative form rather than in structured databases. However, the impending introduction of data warehouses that collect data from a number of organizations across a legal system presents invaluable opportunities for analysts using KDD.
- Description: C1
- Description: 2003000037
Generic arguments : A framework for supporting online deliberative discourse
- Authors: Yearwood, John , Stranieri, Andrew
- Date: 2002
- Type: Text , Conference paper
- Relation: Paper presented at the Thirteenth Australasian Conference on Information Systems, Melbourne : 4th December, 2002
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- Reviewed:
- Description: In this paper we propose a framework based on argumentation that can be used to support deliberative discourse on line. Online communities have several distinct advantages as very open forums but they also have some deep disadvantages. We argue that the proposed framework and web application GAAMtalk permits and encourages the positive elements of online deliberation that will enhance discussions.
- Description: E1
- Description: 2003000114
An algorithm for clustering based on non-smooth optimization techniques
- Authors: Bagirov, Adil , Rubinov, Alex , Sukhorukova, Nadezda , Yearwood, John
- Date: 2003
- Type: Text , Journal article
- Relation: International Transactions in Operational Research Vol. 10, no. 6 (2003), p. 611-617
- Full Text: false
- Reviewed:
- Description: The problem of cluster analysis is formulated as a problem of non-smooth, non-convex optimization, and an algorithm for solving the cluster analysis problem based on non-smooth optimization techniques is developed. We discuss applications of this algorithm in large databases. Results of numerical experiments are presented to demonstrate the effectiveness of this algorithm.
- Description: C1
- Description: 2003000422
Analysis of the Australian credit database
- Authors: Rubinov, Alex , Sukhorukova, Nadezda , Yearwood, John
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at the Symposium on Industrial Optimisation and the 9th Australian Optimisation Day, Perth : 30th September, 2002
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000353
Are schools of education failing the tertiary mathematics sector?
- Authors: Mays, Heather , Yearwood, John
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at 2003 International Symposium on Information Technology, Las Vegas, USA : 28th April, 2003
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- Reviewed:
- Description: In the 1990s, two major issues emerged globally for tertiary mathematics educators: declining standards in the mathematical proficiency of students at tertiary-entry level and the advocates for the incorporation of IT into the processes of teaching and learning. Addressing these issues required significant reform of both curriculum content and classroom practice to ensure that the technology was used appropriately and effectively. These reforms were largely implemented by staff from tertiary Schools of Mathematics. Rather than leading the reform, the Education community lagged behind and in some instances has taken research into the use of IT in Mathematics Education in a questionable direction. In this paper, we outline what we contend has been a failure on the behalf of the Education community to tackle and address problems experienced by mathematics educators (particularly at the tertiary level) and make some suggestions for the directions of future research in Mathematics Education.
- Description: E1
- Description: 2003000464
DOWL : A dynamic ontology language
- Authors: Avery, John , Yearwood, John
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at IADIS International Conference WWW/Internet 2003, Algarve, Portugal : 5th August, 2003
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- Reviewed:
- Description: Abstract: Ontologies in a web setting, particularly those used in a group context (such as a virtual community), need to be flexible and open to changes that reflect the evolution of knowledge. OWL the ontology language of the semantic web provides very little for facilitating the description of evolutionary changes in an ontology. We propose a dynamic web ontology language (dOWL), an extension to OWL, which consists of a set of elements that can be used to model these evolutionary changes in an ontology.
- Description: E1
- Description: 2003000552
Dynamical systems based on a fuzzy derivative and its applications to data classification
- Authors: Mammadov, Musa , Rubinov, Alex , Yearwood, John
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at the Industrial Optimisation 2003 Conference, Perth : 30th September, 2002
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000339
Insights into consumer decisions surrounding adverse drug reactions : Some preliminary results
- Authors: O'Brien, Michelle , Yearwood, John
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at HIC 2003 RACGP 12CC Combined Conferences, Sydney : 10th December, 2003
- Full Text: false
- Reviewed:
- Description: Objectives: This paper presents preliminary findings from the first 10 case studies of Consumers who each suspect they have experienced an adverse drug reaction (ADR). These case studies are part of a larger study involving Consumer/Doctor decisions surrounding adverse drug reactions and prescribing, which is captured in Diagram 1. The key problem identified from our preliminary background work is that there appear to be gaps in our knowledge about the nature of the decisions being made that relate to ADRs, who these decisions are made by, the information required to make these decisions, the completeness of knowledge that is being used and the impact these factors have on the prevention, early detection or management of ADRs. Further investigation will assist in the development of decision support software in this area.
- Description: E1
- Description: 2003000380
New algorithms for multi-class cancer diagnosis using tumor gene expression signatures
- Authors: Bagirov, Adil , Ferguson, Brent , Ivkovic, Sasha , Saunders, Gary , Yearwood, John
- Date: 2003
- Type: Text , Journal article
- Relation: Bioinformatics Vol. 19, no. 14 (2003), p. 1800-1807
- Full Text:
- Reviewed:
- Description: Motivation: The increasing use of DNA microarray-based tumor gene expression profiles for cancer diagnosis requires mathematical methods with high accuracy for solving clustering, feature selection and classification problems of gene expression data. Results: New algorithms are developed for solving clustering, feature selection and classification problems of gene expression data. The clustering algorithm is based on optimization techniques and allows the calculation of clusters step-by-step. This approach allows us to find as many clusters as a data set contains with respect to some tolerance. Feature selection is crucial for a gene expression database. Our feature selection algorithm is based on calculating overlaps of different genes. The database used, contains over 16 000 genes and this number is considerably reduced by feature selection. We propose a classification algorithm where each tissue sample is considered as the center of a cluster which is a ball. The results of numerical experiments confirm that the classification algorithm in combination with the feature selection algorithm perform slightly better than the published results for multi-class classifiers based on support vector machines for this data set.
- Description: C1
- Description: 2003000439
Predicting the Australian stock market index using neural networks and exploiting dynamical swings and intermarket influences
- Authors: Pan, Heping , Tilakaratne, Chandima , Yearwood, John
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at AI 2003: Advances in Artificial Intelligence - the 16th Australian Conference on AI, Perth : 3rd December, 2003
- Full Text: false
- Reviewed:
- Description: This paper presents a computational approach for predicting the Australian stock market index - AORD using multi-layer feed-forward neural networks from the time series data of AORD and various interrelated markets. This effort aims to discover an optimal neural network or a set of adaptive neural networks for this prediction purpose, which can exploit or model various dynamical swings and intermarket influences discovered from professional technical analysis and quantitative analysis. Four dimensions for optimality on data selection are considered: the optimal inputs from the target market (AORD) itself, the optimal set of interrelated markets, the optimal inputs from the optimal interrelated markets, and the optimal outputs. Two traditional dimensions of the neural network architecture are also considered: the optimal number of hidden layers, and the optimal number of hidden neurons for each hidden layer. Three important results were obtained: A 6-day cycle was discovered in the Australian stock market; the time signature used as additional inputs provides useful information; and a minimal neural network using 6 daily returns of AORD and 1 daily returns of SP500 plus the day of the week as inputs exhibits up to 80% directional prediction correctness.
- Description: E1
- Description: 2003000374
Unsupervised and supervised data classification via nonsmooth and global optimisation
- Authors: Bagirov, Adil , Rubinov, Alex , Sukhorukova, Nadezda , Yearwood, John
- Date: 2003
- Type: Text , Journal article
- Relation: Top Vol. 11, no. 1 (2003), p. 1-92
- Full Text:
- Reviewed:
- Description: We examine various methods for data clustering and data classification that are based on the minimization of the so-called cluster function and its modications. These functions are nonsmooth and nonconvex. We use Discrete Gradient methods for their local minimization. We consider also a combination of this method with the cutting angle method for global minimization. We present and discuss results of numerical experiments.
- Description: C1
- Description: 2003000421