Showing items 13241 - 13260 of 17085

Tools for placing legal decision support systems on the world wide web

- Stranieri, Andrew, Yearwood, John, Zeleznikow, John

A case for the re-use of community reasoning

- Stranieri, Andrew, Yearwood, John

  • Authors: Stranieri, Andrew , Yearwood, John
  • Date: 2011
  • Type: Text , Book chapter
  • Relation: Technologies for supporting reasoning communities and collaborative decision making: Cooperative approaches p.
  • Full Text: false
  • Reviewed:
  • Description: In software engineering, the re-use concept is a design principle that improves efficency, quality and maintainability by ensuring that software artifacts are developed once and re-used may times. In an analogous way, a group's reasoning can be imagined to be re-used by that or another group to enhance efficiency, transparency and consistency in decison-making. However, the re-use of reasoning is difficult to achieve because group reasoning cannot easily be captured and the way in which a group reasoning artifact is subsequently used is not obvious. This chapter explores the case for the re-use of community reasoning and concludes that individuals can benefit from a representation of a previous groups's coalesced reasoning to be modeled and the scheme to represent the reasoning have been selected to suit the task. The authors contend that specifying the future community like to re-use the reasoning, called the intended audience, informs a decision regarding whether an exercise aimed at coalescing a group's reasoning is best performed verbally, in writing or with the use of more structured schemes such as Argument visualization.

Explicit representations of reasoning to support deliberation within groups

- Stranieri, Andrew, Yearwood, John, Mays, Heather

  • Authors: Stranieri, Andrew , Yearwood, John , Mays, Heather
  • Date: 2008
  • Type: Text , Conference proceedings
  • Full Text: false
  • Description: In practice, the reasoning that underpins problem solving and decision making is rarely performed by an individual in isolation from others but involves a communicative exchanges between participants in a community that can range in size from two to many thousands. Dialogue theories describe patterns in dialogues comprising many dialectical exchanges and often advance deliberation, the kind of dialogue that ensues when participants actively seek to understand all views and collectively arrive at the rationally optimal solution. This study reports on the use of argument maps for structuring reasoning by groups of secondary students. The study aimed to discover whether different maps facilitate deliberation and enhance understanding of the issues by providing an explicit representation of reasoning. An explicit representation of reasoning is a model that encapsulates all relevant claims, evidence, statutes and principles pertinent to an issue. Schemes that have been used to provide explicit representations of reasoning include the Issue Based Information System (IBIS) map, variants of the Toulmin argument structure (TAS) and other knowledge representation schemes used for intelligent computational systems. Results indicate that an explicit representation of reasoning facilitates a depth of understanding of complex issues and there is some indication that the deliberative quality of discussions is enhanced depending on the level of abstraction of the map. Copyright © 2008 COSI.
  • Description: 2003006482

High definition 3D telemedicine: The next frontier?

- Stranieri, Andrew, Collmann, Richard, Borda, Ann

  • Authors: Stranieri, Andrew , Collmann, Richard , Borda, Ann
  • Date: 2012
  • Type: Text , Conference proceedings
  • Relation: Studies in Health Technology and Informatics, 182, p.133-41.
  • Full Text:
  • Description: Evidence from the literature indicates that the degree of immersion often referred to as the "sense of being there" experienced by clinicians and patients is a factor in the success of tele-health installations. High definition and 3D telemedicine offers a compelling mechanism to achieve a sense of immersion and contribute to an enhanced quality of use. This article surveys HD3D trials in tele-health and concludes that the way HD3D is integrated into telemedicine depends on the clinical, organisational and technological context. In some settings real time HD3D is not so desirable whereas asynchronous transmission of HD3D images and videos is highly desirable. © 2012 The authors and IOS Press.

Capped K-NN Editing in definition lacking environments

- Stranieri, Andrew, Yatsko, Andrew, Golden, Isaac, Mammadov, Musa, Bagirov, Adil

  • Authors: Stranieri, Andrew , Yatsko, Andrew , Golden, Isaac , Mammadov, Musa , Bagirov, Adil
  • Date: 2013
  • Type: Text , Journal article
  • Relation: Journal of Pattern Recognition Research Vol. 8, no. 1 (2013), p. 39-58
  • Full Text: false
  • Reviewed:
  • Description: While any input may be contributing, imprecise specification of class of data subdivided into classes identifies as rather common a source of noise. The misrepresentation may be characteristic of the data or be caused by forcing of a regression problem into the classification type. Consideration is given to examples of this nature, and an alternative is proposed. In the main part, the approach is based on a well-known technique of data treatment for noise using k-NN. The paper advances an editing technique designed around idea of variable number of authenticating instances. Test runs performed on publicly available and proprietary data demonstrate high retention ability of the new procedure without loss of classification accuracy. Noise reduction methods in a broader classification context are extensively surveyed.

Toward computer mediated elicitation of a community's core values for sustainable decision making

- Stranieri, Andrew, Yearwood, John, Afshar, Faye

Insights from jurisprudence for machine learning in law

- Stranieri, Andrew, Zeleznikow, John

Decision support based needs assessment for cancer patients

- Stranieri, Andrew, Kulkarni, Siddhivinayak, Macfadyen, Alyx, Love, Anthony, Vaughan, Stephen

  • Authors: Stranieri, Andrew , Kulkarni, Siddhivinayak , Macfadyen, Alyx , Love, Anthony , Vaughan, Stephen
  • Date: 2011
  • Type: Text , Conference paper
  • Relation: Australasian workshop on health informatics and knowledge management (HIKM)
  • Full Text: false
  • Reviewed:
  • Description: Regular assessment of wellness or quality of life for patients throughout a cancer journey is important so as to identify aspects of life that could lead to distress and impede recovery or acceptance. The emerging trends in assessment are to deploy validated, quality of life instruments on touchscreen computers in medical waiting rooms. However, these add to workload of health care professionals and can be impersonal for patients to use. In this article, an alternate approach is presented that involves a decision support system with natural dialogue that elicits the patient's specific context in a far finer grained manner than is possible with questionnaire based instruments. The system includes a model of heuristics that health care professionals in a locality use to make inferences regarding a patient's quality of life and avenues for referral.
  • Description: E1

An approach for Ewing test selection to support the clinical assessment of cardiac autonomic neuropathy

- Stranieri, Andrew, Abawajy, Jemal, Kelarev, Andrei, Huda, Shamsul, Chowdhury, Morshed, Jelinek, Herbert

  • Authors: Stranieri, Andrew , Abawajy, Jemal , Kelarev, Andrei , Huda, Shamsul , Chowdhury, Morshed , Jelinek, Herbert
  • Date: 2013
  • Type: Text , Journal article
  • Relation: Artificial Intelligence in Medicine Vol. 58, no. 3 (2013), p. 185-193
  • Full Text:
  • Reviewed:
  • Description: Objective: This article addresses the problem of determining optimal sequences of tests for the clinical assessment of cardiac autonomic neuropathy (CAN) We investigate the accuracy of using only one of the recommended Ewing tests to classify CAN and the additional accuracy obtained by adding the remaining tests of the Ewing battery This is important as not all five Ewing tests can always be applied in each situation in practice Methods and material: We used new and unique database of the diabetes screening research initiative project, which is more than ten times larger than the data set used by Ewing in his original investigation of CAN We utilized decision trees and the optimal decision path finder (ODPF) procedure for identifying optimal sequences of tests Results: We present experimental results on the accuracy of using each one of the recommended Ewing tests to classify CAN and the additional accuracy that can be achieved by adding the remaining tests of the Ewing battery We found the best sequences of tests for cost-function equal to the number of tests The accuracies achieved by the initial segments of the optimal sequences for 2, 3 and 4 categories of CAN are 80.80, 91.33, 93.97 and 94.14, and respectively, 79.86, 89.29, 91.16 and 91.76, and 78.90, 86.21, 88.15 and 88.93 They show significant improvement compared to the sequence considered previously in the literature and the mathematical expectations of the accuracies of a random sequence of tests The complete outcomes obtained for all subsets of the Ewing features are required for determining optimal sequences of tests for any cost-function with the use of the ODPF procedure We have also found two most significant additional features that can increase the accuracy when some of the Ewing attributes cannot be obtained Conclusions: The outcomes obtained can be used to determine the optimal sequences of tests for each individual cost-function by following the ODPF procedure The results show that the best single Ewing test for diagnosing CAN is the deep breathing heart rate variation test Optimal sequences found for the cost-function equal to the number of tests guarantee that the best accuracy is achieved after any number of tests and provide an improvement in comparison with the previous ordering of tests or a random sequence © 2013 Elsevier B.V.
  • Description: 2003011130

Data mining Traditional Chinese Medicine (TCM) : Lessons learnt from mining in law and allopathic medicine

- Stranieri, Andrew, Sahama, Tony

  • Authors: Stranieri, Andrew , Sahama, Tony
  • Date: 2012
  • Type: Text , Conference proceedings
  • Full Text: false
  • Description: Key decisions at the collection, pre-processing, transformation, mining and interpretation phase of any knowledge discovery from database (KDD) process depend heavily on assumptions and theoretical perspectives relating to the type of task to be performed and characteristics of data sourced. In this article, we compare and contrast theoretical perspectives and assumptions taken in data mining exercises in the legal domain with those adopted in data mining in TCM and allopathic medicine. The juxtaposition results in insights for the application of KDD for Traditional Chinese Medicine. © 2012 IEEE.
  • Description: 2003009797

Remote monitoring and mobile Apps

- Stranieri, Andrew, Edirisinghe, Ruwini, Wickramasinghe, Nilmini

  • Authors: Stranieri, Andrew , Edirisinghe, Ruwini , Wickramasinghe, Nilmini
  • Date: 2016
  • Type: Text , Book chapter
  • Relation: Contemporary Consumer Health Informatics Chapter 16 p. 297-318
  • Full Text: false
  • Reviewed:
  • Description: Recently, we have been witnessing an exponential growth in mobile health (mHealth) for health care. These solutions are all designed ultimate to enable the consumer to enjoy better health-care delivery and/or wellness. In order to understand this growing area, we believe it is necessary to develop a framework to analyse and evaluate these solutions. The purpose of this chapter is to proffer a suitable taxonomy to do this.

Coalescing medical systems: A challenge for health informatics

- Stranieri, Andrew, Vaughan, Stephen

A model for the introduction of Ayurvedic and Allopathic Electronic Health Records in Sri Lanka

- Stranieri, Andrew, Sahama, Tony, Butler-Henderson, Kerryn, Perera, Kamal

  • Authors: Stranieri, Andrew , Sahama, Tony , Butler-Henderson, Kerryn , Perera, Kamal
  • Date: 2016
  • Type: Text , Conference proceedings
  • Relation: 2016 IEEE International Symposium on Technology and Society; Trivandrum, Kerala, India; 20th-22nd October 2016 p. 56-61
  • Full Text:
  • Reviewed:
  • Description: Fully integrated electronic health records (EHR) provide healthcare providers and patients access to records across a health care system and promise efficient and effective provision of health care. However, fully integrated records have proven to be very expensive and difficult to establish. Currently. EHR's have been developed largely to accommodate Western medicine events. These barriers impact on the introduction of EHR's in Sri Lanka, where health budgets are already stretched and Ayurvedic medicine is routinely practiced alongside Allopathic medicine. This article identifies requirements for EHR in the Sri Lankan context and advances a model for the introduction of EHR's that suits that context. The model is justified by drawing on insights and experiences with EHR in Western nations.

Data-analytically derived flexible HbA1c thresholds for type 2 diabetes mellitus diagnostic

- Stranieri, Andrew, Yatsko, Andrew, Jelinek, Herbert, Venkatraman, Sitalakshmi

  • Authors: Stranieri, Andrew , Yatsko, Andrew , Jelinek, Herbert , Venkatraman, Sitalakshmi
  • Date: 2015
  • Type: Text , Journal article
  • Relation: Artificial Intelligence Research Vol. 5, no. 1 (2015), p. 111-134
  • Full Text:
  • Reviewed:
  • Description: Glycated haemoglobin (HbA1c) is now more commonly used as an alternative test to the fasting plasma glucose and oral glucose tolerance tests for the identification of Type 2 Diabetes Mellitus (T2DM) because it is easily obtained using the point-of-care technology and represents long-term blood sugar levels. According to WHO guidelines, HbA1c values of 6.5% or above are required for a diagnosis of T2DM. However outcomes of a large number of trials with HbA1c have been inconsistent across the clinical spectrum and further research is required to determine the efficacy of HbA1c testing in identification of T2DM. Medical records from a diabetes screening program in Australia illustrate that many patients could be classified as diabetics if other clinical indicators are included, even though the HbA1c result does not exceed 6.5%. This suggests that a cutoff for the general population of 6.5% may be too simple and miss individuals at risk or with already overt, undiagnosed diabetes. In this study, data mining algorithms have been applied to identify markers that can be used with HbA1c. The results indicate that T2DM is best classified by HbA1c at 6.2% - a cutoff level lower than the currently recommended one, which can be even less, having assumed the threshold flexibility, if additionally to HbA1c being high the rule is conditioned on oxidative stress or inflammation being present, atherogenicity or adiposity being high, or hypertension being diagnosed, etc.

Data analytics to select markers and cut-off values for clinical scoring

- Stranieri, Andrew, Yatsko, Andrew, Venkatraman, Sitalakshmi, Jelinek, Herbert

  • Authors: Stranieri, Andrew , Yatsko, Andrew , Venkatraman, Sitalakshmi , Jelinek, Herbert
  • Date: 2018
  • Type: Text , Conference proceedings
  • Relation: ACSW '18: Proceedings of the Australasian Computer Science Week Multiconference; Brisbane; 29th January -2nd February 2018 p. 1-6
  • Full Text: false
  • Reviewed:
  • Description: Scoring systems such as the Glasgow-Coma scale used to assess consciousness AusDrisk to assess the risk of diabetes, are prevalent in clinical practice. Scoring systems typically include relevant variables with ordinal values where each value is assigned a weight. Weights for selected values are summed and compared to thresholds for health care professionals to rapidly generate a score. Scoring systems are prevalent in clinical practice because they are easy and quick to use. However, most scoring systems comprise many variables and require some time to calculate an final score. Further, expensive population-wide studies are required to validate a scoring system. In this article, we present a new approach for the generation of a scoring system. The approach uses a search procedure invoking iterative decision tree induction to identify a suite of scoring rules, each of which requires values on only two variables. Twelve scoring rules were discovered using the approach, from an Australian screening program for the assessment of Type 2 Diabetes risk. However, classifications from the 12 rules can conflict. In this paper we argue that a simple rule preference relation is sufficient for the resolution of rule conflicts.

A process-oriented framework for regulating artificial intelligence systems

- Stranieri, Andrew, Sun, Zhaohao

  • Authors: Stranieri, Andrew , Sun, Zhaohao
  • Date: 2022
  • Type: Text , Book chapter
  • Relation: Handbook of Research on Foundations and Applications of Intelligent Business Analytics p. 96-112
  • Full Text: false
  • Reviewed:
  • Description: Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students. Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students.

Open banking and electronic health records

- Stranieri, Andrew, McInnes, Angelique, Hashmi, Mustafa, Sahama, Tony

Remote patient monitoring for healthcare : a big challenge for big data

- Stranieri, Andrew, Balasubramanian, Venki

  • Authors: Stranieri, Andrew , Balasubramanian, Venki
  • Date: 2022
  • Type: Text , Book chapter
  • Relation: Research Anthology on Big Data Analytics, Architectures, and Applications Chapter 50 p. 1054-1070
  • Full Text: false
  • Reviewed:
  • Description: Remote patient monitoring involves the collection of data from wearable sensors that typically requires analysis in real time. The real-time analysis of data streaming continuously to a server challenges data mining algorithms that have mostly been developed for static data residing in central repositories. Remote patient monitoring also generates huge data sets that present storage and management problems. Although virtual records of every health event throughout an individual’s lifespan known as the electronic health record are rapidly emerging, few electronic records accommodate data from continuous remote patient monitoring. These factors combine to make data analytics with continuous patient data very challenging. In this chapter, benefits for data analytics inherent in the use of standards for clinical concepts for remote patient monitoring is presented. The openEHR standard that describes the way in which concepts are used in clinical practice is well suited to be adopted as the standard required to record meta-data about remote monitoring. The claim is advanced that this is likely to facilitate meaningful real time analyses with big remote patient monitoring data. The point is made by drawing on a case study involving the transmission of patient vital sign data collected from wearable sensors in an Indian hospital. © 2022 by IGI Global. All rights reserved.

How lived experience mediated my gold, ribbons, puzzles and morals research motivations : a reflective introspection

- Stranieri, Andrew

  • Authors: Stranieri, Andrew
  • Date: 2024
  • Type: Text , Book chapter
  • Relation: Research partners with lived experience : stories from patients and survivors Chapter 15 p. 183-191
  • Full Text: false
  • Reviewed:
  • Description: Studies on factors that motivate researchers conclude that financial rewards, recognition, curiosity and a desire to contribute; the so-called, Gold, Ribbons, Puzzle and Morals motivating factors, combine to explain why individuals start and continue to be researchers. Lived experience with significant, often life-changing events as a patient, carer, victim, or bystander has motivated many, directly or indirectly, including me, to become researchers. In this chapter, I draw on introspection to examine my journey through 25 years of research experience in university settings. I use concepts from dual systems theories that identify intuition and cognition as two processes that come together to explain how key events and situations in life have influenced my decisions. This illustrates how critical events have mediated the Gold, Ribbon, Puzzle and Morals factors that were motivating my research efforts.

Emerging point of care devices and artificial intelligence : prospects and challenges for public health

- Stranieri, Andrew, Venkatraman, Sitalakshmi, Minicz, John, Zarnegar, Armita, Firmin, Sally, Balasubramanian, Venki, Jelinek, Herbert

  • Authors: Stranieri, Andrew , Venkatraman, Sitalakshmi , Minicz, John , Zarnegar, Armita , Firmin, Sally , Balasubramanian, Venki , Jelinek, Herbert
  • Date: 2022
  • Type: Text , Journal article
  • Relation: Smart Health Vol. 24, no. (2022), p.
  • Full Text:
  • Reviewed:
  • Description: Risk assessments for numerous conditions can now be performed cost-effectively and accurately using emerging point of care devices coupled with machine learning algorithms. In this article, the case is advanced that point of care testing in combination with risk assessments generated with artificial intelligence algorithms, applied to the universal screening of the general public for multiple conditions at one session, represents a new kind of in-expensive screening that can lead to the early detection of disease and other public health benefits. A case study of a diabetes screening clinic in a rural area of Australia is presented to illustrate its benefits. Universal, poly-aetiological screening is shown to meet the ten World Health Organisation criteria for screening programmes. © Elsevier Inc.