How lived experience mediated my gold, ribbons, puzzles and morals research motivations : a reflective introspection
- 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
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- 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.
Classification of methods to reduce clinical alarm signals for remote patient monitoring : a critical review
- Authors: Arora, Teena , Balasubramanian, Venki , Stranieri, Andrew , Shenhan, Mai , Buyya, Rajkumar , Islam, Sardar
- Date: 2023
- Type: Text , Book chapter
- Relation: Cloud Computing in Medical Imaging Chapter 10 p. 173-194
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A process-oriented framework for regulating artificial intelligence systems
- 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
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- 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.
Deep reinforcement-based conversational ai agent in healthcare system
- Authors: Kulkarni, Pradnya , Stranieri, Andrew , Mahableshwarkar, Ameya , Kulkarni, Mrunalini
- Date: 2022
- Type: Text , Book chapter
- Relation: Studies in Computational Intelligence p. 233-249
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- Description: Conversational AI is a sub-domain of artificial intelligence that deals with speech-based or text-based AI agents that have the capability to simulate and automate conversations and verbal interactions. A Goal Oriented Conversational Agent (GOCA) is a conversational AI agent that attempts to solve a specific problem for the users as per their inputs. The development of Reinforcement Learning algorithms has opened up new opportunities in research related to conversational AI, due to the striking similarity the algorithm bears to the way a conversation takes place. This chapter aims to describe a novel, hybrid conversational AI architecture using Deep Reinforcement Learning that can give state-of-the-art results on the tasks of Intent Classification, Entity Recognition, Dialog Management, State Tracking, Information Retrieval and Natural Language Response Generation. The architecture also consists of external AI modules, focused on carrying out intelligent tasks pertaining to the healthcare sector. The AI tasks that the conversational agent is capable of performing are—Text-based Question Answering, Text Summarization and Visual Question Answering. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Remote patient monitoring for healthcare : a big challenge for big data
- 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
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- 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.
Framework for Integration of Medical Image and Text-Based Report Retrieval to Support Radiological Diagnosis
- Authors: Kulkarni, Siddhivinayak , Savyanavar, Amit , Kulkarni, Pradnya , Stranieri, Andrew , Ghorpade, Vijay
- Date: 2017
- Type: Text , Book chapter
- Relation: Biomedical Signal and Image Processing in Patient Care p. 86-122
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- Description: In healthcare systems, medical devices help physicians and specialists in diagnosis, prognosis, and therapeutics. As research shows, validation of medical devices is significantly optimized by accurate signal processing. Biomedical Signal and Image Processing in Patient Care is a pivotal reference source for progressive research on the latest development of applications and tools for healthcare systems. Featuring extensive coverage on a broad range of topics and perspectives such as telemedicine, human machine interfaces, and multimodal data fusion, this publication is ideally designed for academicians, researchers, students, and practitioners seeking current scholarly research on real-life technological inventions. In healthcare systems, medical devices help physicians and specialists in diagnosis, prognosis, and therapeutics. As research shows, validation of medical devices is significantly optimized by accurate signal processing. Biomedical Signal and Image Processing in Patient Care is a pivotal reference source for progressive research on the latest development of applications and tools for healthcare systems. Featuring extensive coverage on a broad range of topics and perspectives such as telemedicine, human machine interfaces, and multimodal data fusion, this publication is ideally designed for academicians, researchers, students, and practitioners seeking current scholarly research on real-life technological inventions.
A taxonomy for mHealth
- Authors: Edirisinghe, Ruwini , Stranieri, Andrew , Wickramasinghe, Nilmini
- Date: 2016
- Type: Text , Book chapter
- Relation: Handbook of Research on Healthcare Administration and Management Chapter 36 p. 596-615
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- Description: Recently, we are witnessing an exponential growth in remote monitoring and mobile applications for healthcare. These solutions are all designed to ultimately enable the consumer to enjoy better healthcare 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 then is to offer a suitable taxonomy to systematically analyse and evaluate the existing solutions based on number of dimensions including technological, clinical, social, and economic.
Remote monitoring and mobile Apps
- Authors: Stranieri, Andrew , Edirisinghe, Ruwini , Wickramasinghe, Nilmini
- Date: 2016
- Type: Text , Book chapter
- Relation: Contemporary Consumer Health Informatics Chapter 16 p. 297-318
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- 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.
Teleconsultation and telediagnosis for oral health assessment: An australian perspective
- Authors: Mariño, Rodrigo , Clarke, Ken , Manton, David , Stranieri, Andrew , Collmann, Richard , Kellet, H , Borda, Ann
- Date: 2015
- Type: Text , Book chapter
- Relation: Teledentistry p. 101-112
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- Description: Oral health informatics is the application of Information and Communication Technology (ICT) for problem solving complex and dynamic information and system interactions in dental science and oral health, research and education. In the last few years, there has been rapid development and expansion of the uses of Information and Communication Technology (ICT) and it is presently used in many areas of oral health care practice. ICT offers new opportunities to improve oral health care by enhancing early diagnosis, facilitating timely treatment of oral diseases, and reducing isolation of practitioners through communication with peers and consultation with specialists. Above all, ICT offers improved access to care as an effective alternative to classic face-to-face oral health professional-patient interaction, in terms of both clinical results and cost-effectiveness. Still, compared to medicine, teledentistry is rarely used in everyday oral health practice.This chapter reviews developments in teledentistry, outlines the benefits of applications in teledentistry and provides information on the rationale for the use of teledentistry. A second part provides an overview of teledentistry and its uses in different scenarios based on experiences in various research projects in the areas of teleconsultation and telediagnosis in Australia. These are projects that represent responses to the serious dental workforce shortage in underserved Australian communities and are equally applicable to many countries facing the same issue. © Springer International Publishing Switzerland 2015.
Real-time self-stabilizing scheme for the localization of faults in wireless sensor networks
- Authors: Saeed, Ather , Stranieri, Andrew , Dazeley, Richard
- Date: 2014
- Type: Text , Book chapter
- Relation: Recents advances in Image, Audio and Signal Processing p. 233-242
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- Description: Reliable acquisition of data from massively dense wireless sensor networks (WSN) is a challenge due to the unpredictable behaviour of nodes responsible for collecting and disseminating datasets of interest. Therefore, accurate sensing of events from nodes depend on several microscopic and macroscopic factors such as distance of a node from the sink, radio signal strength and connectedness of network for routing datasets to the nearest sink. Several Clustering schemes have been proposed for routing datasets, where major focus was on finding the next cluster-head with maximum energy for routing data. Such schemes are not suitable for the real-time dissemination of datasets because electing the next cluster-head is a computational intensive process. A new energy-efficient self-stabilizing sliding rectangle protocol (ESSRP) is proposed in this paper for ensuring reliability and connectedness of regions for minimizing data loss and prolonging network life. The proposed scheme not only looks at the energy-balance of a particular cluster but also ensures fault-localization and tolerance by providing self-stabilization to network in the event of nodes or links failure using Green’s Theorem. The WSN rectangular regions should be oriented counter-clockwise, piecewise regular and continuously differentiable so that faults can be efficiently localized, identified and rectified in a particular region
Detection of CAN by ensemble classifiers based on Ripple Down rules
- Authors: Kelarev, Andrei , Dazeley, Richard , Stranieri, Andrew , Yearwood, John , Jelinek, Herbert
- Date: 2012
- Type: Text , Book chapter
- Relation: Knowledge Management and Acquisition for Intelligent Systems p. 147-159
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- Description: It is well known that classification models produced by the Ripple Down Rules are easier to maintain and update. They are compact and can provide an explanation of their reasoning making them easy to understand for medical practitioners. This article is devoted to an empirical investigation and comparison of several ensemble methods based on Ripple Down Rules in a novel application for the detection of cardiovascular autonomic neuropathy (CAN) from an extensive data set collected by the Diabetes Complications Screening Research Initiative at Charles Sturt University. Our experiments included essential ensemble methods, several more recent state-of-the-art techniques, and a novel consensus function based on graph partitioning. The results show that our novel application of Ripple Down Rules in ensemble classifiers for the detection of CAN achieved better performance parameters compared with the outcomes obtained previously in the literature.
Insights from jurisprudence for machine learning in law
- Authors: Stranieri, Andrew , Zeleznikow, John
- Date: 2012
- Type: Text , Book chapter
- Relation: Machine Learning Algorithms for Problem Solving in Computational Applications: Intelligent Techniques p. 85-98
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- Description: The central theme of this chapter is that the application of machine learning to data in the legal domain involves considerations that derive from jurisprudential assumptions about the nature of legal reasoning. Jurisprudence provides a unique resource for machine learning in that, for over one hundred years, significant thinkers have advanced concepts including open texture and discretion. These concepts inform and guide applications of machine learning to law.
A case for the re-use of community reasoning
- Authors: Stranieri, Andrew , Yearwood, John
- Date: 2011
- Type: Text , Book chapter
- Relation: Technologies for supporting reasoning communities and collaborative decision making: Cooperative approaches p.
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- 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.
A reasoning community perspective on deliberate democracy
- Authors: Yearwood, John , Stranieri, Andrew
- Date: 2011
- Type: Text , Book chapter
- Relation: Technologies for supporting reasoning communities and collaborative decision making: Cooperative approaches p.237-246
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- Description: This chapter describes some of the current approaches to delibertative democracy and the considers them from the perspective of a reasoning community framework. This approach highlights important tasks, process and structures that can be used to enhance the process of groups engaging in deliberative democracy approaches. In particular it focuses attention on the potential for technologies to support groups in achieving broad agreed structured reasoning bases that capture the scope of an issue from multiple perspectives.
A Tool for Assisting Group Decision-Making for Consensus Outcomes in Organizations
- Authors: Afshar, Faye , Yearwood, John , Stranieri, Andrew
- Date: 2006
- Type: Text , Book chapter
- Relation: E-Supply Chain Technologies and Management p. 316-343
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Supporting the design OHS process: a knowledge-based system for risk management
- Authors: Lingard, Helen , Stranieri, Andrew , Blismas, Nick
- Date: 2006
- Type: Text , Book chapter
- Relation: Clients driving construction innovation: moving ideas into practice p.
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