ORCID Profile
0000-0003-0175-8692
Current Organisation
University of Tasmania
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Publisher: IEEE
Date: 2008
DOI: 10.1109/MUE.2008.93
Publisher: Global Vision Press
Date: 31-12-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: IEEE
Date: 12-2008
Publisher: Elsevier BV
Date: 12-2021
DOI: 10.1016/J.CORTEX.2021.09.018
Abstract: Previous research suggests oral and written language can act as barometers of an in idual's cognitive function, potentially providing a screening tool for the earliest stages of Alzheimer's disease (AD) and other forms of dementia. Idea density is a measure of the rate at which ideas, or elementary predications, are expressed and may provide an ideal measure for early detection of deficits in language. Previous research has shown that when no restrictions are set on the topic of the idea, a decrease in propositional idea density (PID) is associated with an increased risk of developing AD. However, this has been limited by moderate s le sizes and manual transcribing. Technological advancement has enabled the automated calculation of PID from tools such as the Computerized Propositional Idea Density Rater (CPIDR). We delivered an online autobiographical writing task to older adult Australians from ISLAND (Island Study Linking Ageing and Neurodegenerative Disease). Linear regression models were fitted in R. We analysed text files (range 10-1180 words) using CPIDRv5 provided by 3316 (n = 853 males [25.7%], n = 2463 females [74.3%]) ISLAND participants. Over 358,957 words written in 3316 written autobiographical responses were analysed. Mean PID was higher in females (53.5 [±3.69]) than males (52.6 [±4.50]). Both advancing age and being male were significantly associated with a decrease in PID (p < .001). Automated methods of language analysis hold great promise for the early detection of subtle deficits in language capacity. Although our effect sizes were small, PID may be a sensitive measure of deficits in language in ageing in iduals and is able to be collected at scale using online methods of data capture.
Publisher: Springer International Publishing
Date: 2022
Publisher: Springer International Publishing
Date: 2022
Publisher: Springer International Publishing
Date: 2022
Publisher: Elsevier BV
Date: 04-2009
Publisher: ACM
Date: 23-11-2009
Publisher: Public Library of Science (PLoS)
Date: 27-02-2023
DOI: 10.1371/JOURNAL.PONE.0282436
Abstract: Preclinical Alzheimer’s disease (AD) represents the earliest phase of AD, often years before the onset of mild cognitive impairment (MCI). There is a pressing focus on identifying in iduals in the preclinical AD phase to alter the trajectory or impact of the disease potentially. Increasingly, Virtual Reality (VR) technology is being used to support a diagnosis of AD. While VR technology has been applied to the assessment of MCI and AD, studies about how best to utilize VR as a screening tool for preclinical AD are limited and discordant. The objectives of this review are to synthesize the evidence pertaining to the use of VR as a screening tool for preclinical AD as well as to identify factors that need to be considered when utilizing VR to screen for preclinical AD. The methodological framework proposed by Arksey and O’Malley (2005) will be introduced to guide the conduction of the scoping review, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) (2018) will be used to organize and structure the review. PubMed, Web of Science, Scopus, ScienceDirect and Google Scholar will be used to search for literature. Obtained studies will be screened for eligibility based on predefined exclusion criteria. A narrative synthesis of eligible studies will be performed, after tabulating the extracted data from existing literature, to answer the research questions. Ethical approval is not required for this scoping review. Findings will be disseminated through conference presentations, publication in a peer-reviewed journal, and discussions among professional networks in the research domain combining neuroscience and information and communications technology (ICT). This protocol has been registered on Open Science Framework (OSF). Relevant materials and potential following updates are available at osf.io/aqmyu .
Publisher: IEEE
Date: 09-2009
Publisher: Inderscience Publishers
Date: 2009
Publisher: AIP
Date: 2007
DOI: 10.1063/1.2816646
Publisher: IEEE
Date: 07-2010
Publisher: Springer International Publishing
Date: 2019
Publisher: IEEE
Date: 07-2010
Publisher: IEEE
Date: 11-2008
Publisher: Elsevier BV
Date: 06-2003
Publisher: IEEE
Date: 2010
Publisher: Elsevier BV
Date: 03-2024
Publisher: Public Library of Science (PLoS)
Date: 21-07-2011
Publisher: IEEE
Date: 04-2009
Publisher: IEEE
Date: 2009
Publisher: ACM
Date: 17-10-2017
Publisher: IEEE
Date: 08-2010
DOI: 10.1109/CGIV.2010.26
Publisher: ACM
Date: 23-11-2009
Publisher: MDPI AG
Date: 14-08-2023
DOI: 10.3390/ANI13162622
Abstract: The analysis of AR is widely used to detect loss of acrosome in sperm, but the subjective decisions of experts affect the accuracy of the examination. Therefore, we develop an ARCS for objectivity and consistency of analysis using convolutional neural networks (CNNs) trained with various magnification images. Our models were trained on 215 microscopic images at 400× and 438 images at 1000× magnification using the ResNet 50 and Inception–ResNet v2 architectures. These models distinctly recognized micro-changes in the PM of AR sperms. Moreover, the Inception–ResNet v2-based ARCS achieved a mean average precision of over 97%. Our system’s calculation of the AR ratio on the test dataset produced results similar to the work of the three experts and could do so more quickly. Our model streamlines sperm detection and AR status determination using a CNN-based approach, replacing laborious tasks and expert assessments. The ARCS offers consistent AR sperm detection, reduced human error, and decreased working time. In conclusion, our study suggests the feasibility and benefits of using a sperm diagnosis artificial intelligence assistance system in routine practice scenarios.
Publisher: IEEE
Date: 07-2010
Publisher: IEEE
Date: 2006
DOI: 10.1109/CGIV.2006.63
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: IEEE
Date: 10-2008
Publisher: IEEE
Date: 10-2008
DOI: 10.1109/UMC.2008.26
Publisher: Springer International Publishing
Date: 2018
Publisher: IEEE
Date: 05-2007
Publisher: IEEE
Date: 12-2010
Publisher: International Society for Problem-Based Learning
Date: 30-10-2021
Abstract: ObjectiveInvestigate the capability of a knowledge-based framework and architecture, used in a specific health domain problem that can utilise transfer learning, to speed virtual patient development for problem-based training and assessment in other health domains.MethodsAnalysis of a case study, based on a virtual patient used in the training of pharmacy students, to discover the viability of using generic, ontological knowledge capable of transfer to virtual patients in other health domains.ResultsAreas of the virtual pharmacy patient knowledge-base were identified, along with corresponding expected student questions, that are generic to other health domains. Using the framework from the case study to develop a new virtual patient for problem-based learning and assessment in a new health domain, these generic target questions could be utilised to speed up the development of other learning stimuli in future projects involving different health domains, such as nurse training in pain management.ConclusionsWith some modification, the framework of the case-study virtual patient was found to be capable of supporting generic expected student questions capable of re-use in virtual patients with new clinical conditions.
Publisher: IEEE Comput. Soc
Date: 2002
Publisher: SPIE
Date: 09-06-2003
DOI: 10.1117/12.480173
No related grants have been discovered for Mira Park.