Towards smart online dispute resolution for medical disputes
- Authors: Bellucci, Emilia , Stranieri, Andrew , Venkatraman, Sitalakshmi
- Date: 2020
- Type: Text , Conference proceedings , Conference paper
- Relation: Proceedings of the Australasian Computer Science Week Multiconference (ACSW 2020); Melbourne, Australia; 3rd-7th February 2020. p. 1-5
- Full Text: false
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- Description: With the advancements in technologies, digitization of health records in the healthcare industry is undertaking a rapid revolution. This is further fueled with the entrance of Internet of Things (IoT), where mobile health devices have resulted in an explosion of health data and increased accessibility via wireless communications and sensor networks. With the introduction of an Electronic Health Record (EHR) system as an important venture for the general health and wellbeing of a country's citizens, privacy issues and medical disputes are expected to rise. In addition to critical health information being documented and shared electronically, integrating data from diverse smart medical IoT devices are leading towards increasingly more complex disputes that require immense time and effort to resolve. Online dispute resolution (ODR) programs have been successfully applied to cost-effectively help disputants resolve commercial, insurance and other legal disputes, but as yet have not been applied to healthcare. This paper takes a modest step in this direction, firstly to identify the drivers of medical disputes that include patient empowerment and technology advancements and trends. Secondly, we explore dispute resolution models and identify the status and limitations of current ODR systems.
- Description: This work was funded by the University of Ballarat Deakin University Collaborative Fund. 160134
Classification for accuracy and insight : A weighted sum approach
- Authors: Quinn, Anthony , Stranieri, Andrew , Yearwood, John
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at Sixth Australasian Data Mining Conference, AusDM 2007, Gold Coast, Queensland, Victoria : 3rd-4th December 2007 p. 203-208
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- Description: This research presents a classifier that aims to provide insight into a dataset in addition to achieving classification accuracies comparable to other algorithms. The classifier called, Automated Weighted Sum (AWSum) uses a weighted sum approach where feature values are assigned weights that are summed and compared to a threshold in order to classify an example. Though naive, this approach is scalable, achieves accurate classifications on standard datasets and also provides a degree of insight. By insight we mean that the technique provides an appreciation of the influence a feature value has on class values, relative to each other. AWSum provides a focus on the feature value space that allows the technique to identify feature values and combinations of feature values that are sensitive and important for a classification. This is particularly useful in fields such as medicine where this sort of micro-focus and understanding is critical in classification.
- Description: 2003005504
Exploring novel features and decision rules to identify cardiovascular autonomic neuropathy using a hybrid of wrapper-filter based feature selection
- Authors: Huda, Shamsul , Jelinek, Herbert , Ray, Biplob , Stranieri, Andrew , Yearwood, John
- Date: 2010
- Type: Text , Conference paper
- Relation: Paper presented at the 2010 6th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2010 p. 297-302
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- Description: Cardiovascular autonomic neuropathy (CAN) is one of the important causes of mortality among diabetes patients. Statistics shows that more than 22% of people with type 2 diabetes mellitus suffer from CAN and which in turn leads to cardiovascular disease (heart attack, stroke). Therefore early detection of CAN could reduce the mortality. Traditional method for detection of CAN uses Ewing's algorithm where five noninvasive cardiovascular tests are used. Often for clinician, it is difficult to collect data from for the Ewing Battery patients due to onerous test conditions. In this paper, we propose a hybrid of wrapper-filter approach to find novel features from patients' ECG records and then generate decision rules for the new features for easier detection of CAN. In the proposed feature selection, a hybrid of filter (Maximum Relevance, MR) and wrapper (Artificial Neural Net Input Gain Measurement Approximation ANNIGMA) approaches (MR-ANNIGMA) would be used. The combined heuristics in the hybrid MRANNIGMA takes the advantages of the complementary properties of the both filter and wrapper heuristics and can find significant features. The selected features set are used to generate a new set of rules for detection of CAN. Experiments on real patient records shows that proposed method finds a smaller set of features for detection of CAN than traditional method which are clinically significant and could lead to an easier way to diagnose CAN. © 2010 IEEE.
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
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- Description: E1
- Description: 2003000112
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
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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- 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
Online group deliberation for the elicitation of shared values to underpin decision making
- Authors: Feldman, Yishai , Kraft, Donald , Kuflik, Tsvi , Afshar, Faezeh , Stranieri, Andrew , Yearwood, John
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at 7th International Conference, NGITS 2009, Next generation information technologies and systems, Haifa, Israel : 16th-18th June 2009 Vol. 5831, p. 158-168
- Full Text: false
- Description: Values have been shown to underpin our attitudes, behaviour and motivate our decisions. Values do not exist in isolation but have meaning in relation to other values. However, values are not solely the purview of individuals as communities and organisations have core values implicit in their culture, policies and practices. Values for a group can be determined by a minority in power, derived by algorithmically merging values each group member holds, or set by deliberative consensus. The elicitation of values for the group by deliberation is likely to lead to widespread acceptance of values arrived at, however enticing individuals to engage in face to face discussion about values has been found to be very difficult. We present an online deliberative communication approach for the anonymous deliberation of values and claim that the framework has the elements required for the elicitation of shared values.
- Description: 2003007509
Knowledge discovery from legal databases
- Authors: Stranieri, Andrew , Zeleznikow, John
- Date: 2005
- Type: Text , Book
- Full Text: false
- Reviewed:
- Description: A1
- Description: 2003000833
The integration of narrative and argumentation for a scenario-based learning environment in law
- Authors: Stranieri, Andrew , Yearwood, John
- Date: 2005
- Type: Text , Conference paper
- Relation: Paper presented at the Tenth International Conference on Artificial Intelligence and Law, Bologna, Italy : 6th - 11th June, 2005
- Full Text: false
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- Description: Narrative or story telling has long been used to structure and organise human experience. In contrast to logical models of reasoning, narrative models enable complex situations to be understood and recalled by humans readily. There is also some indication that narrative models represent the way in which jurors weigh up the veracity of legal evidence. In this work a narrative model is integrated into a logical reasoning model for the purpose of advancing a learning environment that promises to be engaging and effective. The narrative model includes a representation of the point of a story and a simple story grammar. The learning environment is designed to enable the automated generation of plausible scenarios representing a variety of family law property division cases told from the point of view of numerous characters.
- Description: E1
- Description: 2003001432
Structured reasoning to support deliberative dialogue
- Authors: Macfadyen, Alyx , Stranieri, Andrew , Yearwood, John
- Date: 2005
- Type: Text , Journal article
- Relation: Lecture Notes in Artificial Intelligence 3681: Knowledge-Based Intelligent Information and Engineering Systems, 9th International Conference, KES 2005, Melbourne, Australia, September 2005, Proceedings, Part 1 Vol. 1, no. (2005), p. 283-289
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- Description: Deliberative dialogue is a form of dialogue that involves participants advancing claims and, without power plays or posturing, deliberating on the claims of others until a consensus decision is reached. This paper describes a deliberative support system to facilitate and encourage participants to engage in a discussion deliberatively. A knowledge representation framework is deployed to generate a strong domain model of reasoning structure. The structure, coupled with a deliberative dialogue protocol results in a web based system that regulates a discussion to avoid combative, non-deliberative exchanges. The system has been designed for online dispute resolution between husband and wife in divorce proceedings involving property.
- Description: C1
- Description: 2003001381
Deliberative discourse and reasoning from generic argument structures
- Authors: Yearwood, John , Stranieri, Andrew
- Date: 2009
- Type: Text , Journal article
- Relation: AI and Society Vol. 23, no. 3 (2009), p. 353-377
- Full Text: false
- Reviewed:
- Description: In this article a dialectical model for practical reasoning within a community, based on the Generic/Actual Argument Model (GAAM) is advanced and its application to deliberative dialogue discussed. The GAAM, offers a dynamic template for structuring knowledge within a domain of discourse that is connected to and regulated by a community. The paper demonstrates how the community accepted generic argument structure acts to normatively influence both admissible reasoning and the progression of dialectical reasoning between participants. It is further demonstrated that these types of deliberation dialogues supported by the GAAM comply with criteria for normative principles for deliberation, specifically, Alexy's rules for discourse ethics and Hitchcock's Principles of Rational Mutual Inquiry. The connection of reasoning to the community in a documented and transparent structure assists in providing best justified reasons, principles of deliberation and ethical discourse which are important advantages for reasoning communities. © Springer-Verlag London Limited 2006.
Web-based decision support for structured reasoning in health
- Authors: Stranieri, Andrew , Yearwood, John , Gervasoni, Susan , Garner, Susan , Deans, Cecil , Johnstone, Alistair
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at Health Informatics Conference 2004 - Let's make a difference with health ICT, Brisbane, Queensland : 25th July, 2004
- Full Text: false
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- Description: Decision making processes in the health care setting are often complex, demanding of professionals and rapidly changing. Furthermore, there is increasing pressure for professionals to make reasoning transparent and consistent. Decision support technologies have not made a substantial contribution to these issues to date largely because knowledge is difficult to elicit and maintain and existing development tools are very sophisticated yet complex. In this study a method for representing complex and discretionary reasoning used successfully in law was applied to the task of modelling decision making processes that critical care nurses deploy in responding to a low oxygen alarm. The approach, based on decision and argument tree diagrams enables the rapid development of small scale, yet useful web based decision support systems.
- Description: E1
- Description: 2003000831
Group structured reasoning for coalescing group decisions
- Authors: Yearwood, John , Stranieri, Andrew
- Date: 2009
- Type: Text , Journal article
- Relation: Group Decision and Negotiation Vol. , no. (2009), p. 1-29
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- Description: In this paper we present the notion of structured reasoning through a model, called the Generic/Actual Argument Model (GAAM). The model which has been used as a computational representation for machine modelling of reasoning and for hybrid combinations of human and machine reasoning can be used as a coalescent framework for decision making. Whilst the notion of structuring reasoning is not new, structured reasoning is advanced as a technique where group consensus on reasoning structures at various levels can be used to facilitate the comprehension of complex reasoning particularly where there are multiple perspectives. For an issue, the approach provides a scaffolding structure for cognitive co-operation and a normative reasoning structure against which group participants can identify points of difference and points in common as well as the nature of the differences and similarities. Intra-group transparency characterized by the ability to recognise points in common and understand the nature of differences is important to the process of coalescing group decisions that carry maximum group support. © 2009 Springer Science+Business Media B.V.
Visualizing association rules for feedback within the legal system
- Authors: Ivkovic, Sasha , Yearwood, John , Stranieri, Andrew
- Date: 2003
- Type: Text , Conference paper
- Relation: Paper presented at the 9th International Conference on Artificial Intelligence and Law, Edinburgh, Scotland : 24th - 28th June, 2003
- Full Text: false
- Reviewed:
- Description: Knowledge discovery from databases (KDD) exercises in law have typically attempted to derive knowledge about decision making processes in the legal domain automatically from datasets. This is made difficult in that real data that represents aspects of a decision process in law is commonly stored as text and rarely stored in structured databases. The central claim advanced here is that KDD processes can be usefully applied to existing datasets of client and demographic data in order to provide feedback for the effective operation of organizations within the legal system. However, the cost of data mining suites and the scarcity of specialized personnel for these tools mitigates against their use. In this study data mining with Association Rules (AR) has been performed on a data-set of over 380,000 records from a legal aid agency. Methods to visualise patterns in order to suggest and test plausible hypotheses from the data have been developed. The tool, called WebAssociate is entirely web based. Domain experts using the tool report favorable responses.
- Description: E1
- Description: 2003000495
Feature selection using misclassification counts
- Authors: Bagirov, Adil , Yatsko, Andrew , Stranieri, Andrew
- Date: 2011
- Type: Conference proceedings , Unpublished work
- Relation: Proceedings of the 9th Australasian Data Mining Conference (AusDM 2011), 51-62. Conferences in Research and Practice in Information Technology (CRPIT), Vol. 121.
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- Description: Dimensionality reduction of the problem space through detection and removal of variables, contributing little or not at all to classification, is able to relieve the computational load and instance acquisition effort, considering all the data attributes accessed each time around. The approach to feature selection in this paper is based on the concept of coherent accumulation of data about class centers with respect to coordinates of informative features. Ranking is done on the degree to which different variables exhibit random characteristics. The results are being verified using the Nearest Neighbor classifier. This also helps to address the feature irrelevance and redundancy, what ranking does not immediately decide. Additionally, feature ranking methods from different independent sources are called in for the direct comparison.
- Description: Dimensionality reduction of the problem space through detection and removal of variables, contributing little or not at all to classification, is able to relieve the computational load and the data acquisition effort, considering all data components being accessed each time around. The approach to feature selection in this paper is based on the concept of coherent accumulation of data about class centers with respect to coordinates of informative features. Ranking is done on the degree, to which different variables exhibit random characteristics. The results are being verified using the Nearest Neighbor classifier. This also helps to address the feature irrelevance, what ranking does not immediately decide. Additionally, feature ranking methods available from different independent sources are called in for direct comparison.
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
Supporting discretionary decision-making with information technology
- Authors: Hall, Mary Jean , Calabro, Domenico , Sourdin, Tania , Stranieri, Andrew , Zeleznikow, John
- Date: 2005
- Type: Text , Journal article
- Relation: University of Ottawa Law & Technology Journal Vol. 2, no. 1 (2005), p. 1-36
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- Description: A NUMBER OF INCREASINGLY SOPHISTICATED technologies are now being used to support complex decision-making in a range of contexts. This paper reports on a project undertaken to provide decision support in discretionary legal domains by referring to a recently created model that involves the interplay and weighting of relevant rule-based and discretionary factors used in a decision-making process. The case study used in the modelling process is the Criminal Jurisdiction of the Victorian Magistrate’s Court (Australia), where the handing down of an appropriate custodial or non-custodial sentence requires the consideration of many factors. Tools and techniques used to capture relevant expert knowledge and to display it both as a paper model and as an online prototype application are discussed. Models of sentencing decision-making with rule-based and discretionary elements are presented and analyzed. This paper concludes by discussing the benefits and disadvantages of such technology and considers some potential appropriate uses of the model and web-based prototype application.
- Description: C1
- Description: 2003001431
ToolSHeD The development and evaluation of a decision support tool for health and safety in construction design
- Authors: Cooke, Tracy , Lingard, Helen , Blismas, Nick , Stranieri, Andrew
- Date: 2008
- Type: Journal article
- Relation: Engineering Construction & Architectural Management Vol. 15, no. 4 (2008), p. 336-351
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- Description: Purpose - The purpose of this paper is to describe an innovative information and decision support tool (ToolSHeD™) developed to help construction designers to integrate the management of OHS risk into the design process. The underlying structure of the prototype web-based system and the process of knowledge acquisition and modelling are described. Design/methodology/approach - The ToolSHeD™ research and development project involved the capture of expert reasoning regarding design impacts upon occupational health and safety (OHS) risk. This knowledge was structured using an innovative method well-suited to modelling knowledge in the context of uncertainty and discretionary decision-making. Example "argument trees" are presented, representing the reasoning used by a panel of experts to assess the risk of falling from height during roof maintenance work, The advantage of using this method for modelling OHS knowledge, compared to the use of simplistic rules, is discussed Findings - The ToolSHeD™ prototype'development and testing reveals that argument trees can represent design safety risk knowledge effectively. Practical implications - The translation of argument trees into a web-based decision support tool is described and the potential impact of this tool in providing construction designers (architects and engineers) with easy and inexpensive access to expert OHS knowledge is discussed. Originality/value - The paper describes a new computer application, currently undergoing testing in the Australian building and construction industry. Its originality lies in the fact that ToolSHeD™ deploys argument trees to represent expert OHS reasoning, overcoming inherent limitations in rule-based expert systems.
- Description: 2003006485
An intelligent learning environment for traditional Chinese medicine practitioners and students
- Authors: Jia, Long , Stranieri, Andrew , Shen, J
- Date: 2008
- Type: Text , Conference paper
- Relation: Paper presented at HIC 2008 Australia's Health Informatics Conference; The Person in the Centre, Brunswick East, Victoria : 31st August - 2nd September 2008
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- Description: Objectives: This study aims to support the training of Traditional Chinese Medicine practitioners by embedding an expert diagnostic model for arthritis into an Intelligent Interactive Learning Environment (IILE). Background: The increasing prevalence of Traditional Chinese Medicine (TCM) outside China is characterised by the emergence of university level practitioner training and stringent regulatory requirements. TCM differential diagnosis is a difficult task that was traditionally taught by exposure to large numbers of patients in a master-apprentice context. In university degree programs, students and novice diagnosticians cannot have the exposure to cases possible in the traditional context. An online system that engages students in the interactive construction of a virtual case and provides immediate feedback on the appropriateness of student actions and the accuracy of diagnostic conclusions can enhance student learning. The system, an Intelligent Interactive Learning Environment (IILE) is based on an approach that has been shown to improve learning outcomes in intensive care nurse training. Methods: An expert model of diagnostic reasoning elicited from TCM expert practitioners lies at the core of the IILE. The knowledge acquisition is performed using an argumentation tree representation that has been shown to be effective in structuring complex knowledge and facilitating engineer - expert interactions. Problems associated with keeping knowledge bases up to date are mitigated with the use of a knowledge model known as ripple down rules permits dynamic updating of knowledge so that knowledge bases evolve over time. A simple narrative model builds up the virtual case study as user interaction proceeds. Results and discussion: This article reports preliminary results in the study that includes an overview of TCM differential diagnosis, the argument tree, the ripple down rule representation and the narrative based IILE. Segments of the knowledge model based solely on TCM literature are illustrated.
- Description: 2003006755
Enhancing learning outcomes with an interactive knowledge-based learning environment providing narrative feedback
- Authors: Stranieri, Andrew , Yearwood, John
- Date: 2008
- Type: Text , Journal article
- Relation: Interactive Learning Environments Vol. 16, no. 3 (2008), p. 265-281
- Full Text: false
- Reviewed:
- Description: This paper describes a narrative-based interactive learning environment which aims to elucidate reasoning using interactive scenarios that may be used in training novices in decision-making. Its design is based on an approach to generating narrative from knowledge that has been modelled in specific decision/reasoning domains. The approach uses a narrative model that is guided partially by inference and contextual information contained in the particular knowledge representation used, the generic/actual argument model of structured reasoning. The approach is described with examples in the area of critical care nursing training. A study of the effectiveness of this approach on learning outcomes was conducted with final year nursing students and provides evidence of improved learning outcomes.
- Description: C1