115 resultados para Radiographic Image Interpretation, Computer-Assisted

em Deakin Research Online - Australia


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Histopathological scoring of disease stage uses descriptive categories without measuring the amount of fibrosis. Collagen, the major component of fibrous tissue, can be quantified by computer-assisted digital image analysis (DIA) using histological sections. We determined relationships between DIA, Ishak stage, and hepatic venous pressure gradient (HVPG) reflecting severity of fibrosis. One hundred fifteen patients with hepatitis C virus (HCV) who had undergone transplantation had 250 consecutive transjugular liver biopsies combined with HVPG (median length, 22 mm; median total portal tracts, 12), evaluated using the Ishak system and stained with Sirus red for DIA. Liver collagen was expressed as collagen proportionate area (CPA). Median CPA was 6% (0.2-45), correlating with Ishak stage (stage 6 range, 13%-45%), and with HVPG (r = 0.62; P < 0.001). Median CPA was 4.1% when HVPG was less than 6 mm Hg and 13.8% when HVPG was 6 mm Hg or more (P < 0.0001) and 6% when HVPG was less than 10 mm Hg and 17.3% when HVPG was 10 mm Hg or higher (P < 0.0001). Only CPA, not Ishak stage/grade, was independently associated by logistic regression, with HVPG of 6 mm Hg or more [odds ratio, 1.206; 95% confidence interval (CI), 1.094-1.331; P < 0.001], or HVPG of 10 mm Hg or more (odds ratio, 1.105; 95% CI, 1.026-1.191; P = 0.009). CPA increased by 50% (3.6%) compared with 20% in HVPG (1 mm Hg) in 38 patients with repeated biopsies. Conclusion: CPA assessed by DIA correlated with Ishak stage scores and HVPG measured contemporaneously. CPA was a better histological correlate with HVPG than Ishak stage, had a greater numerical change when HVPG was low, and resulted in further quantitation of fibrosis in cirrhosis.

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This study examines the factors affecting student performance in an undergraduate financial accounting course, utilising Computer Assisted Learning (CAL). Multiple regression analysis on student performance shows that positive perceptions of the usefulness of CAL significantly influenced performance. It was also found that International students had significantly poorer performance than local students. This result may be attributed to transitional problems experienced by these students, given their different pathways to university study Prior studies of accounting and computing at secondary school level, together with gender, were not significant influences on performance. The results have implications for accounting educators utilising CAL in courses as a means of improving students understanding of accounting concepts and as a means of providing efficient and effective educational instruction to maximise learning outcomes in accounting.

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This study examines student perceptions of the usefulness of Computer-Assisted Learning (CAL) packages in learning accounting concepts in terms of the influence on academic performance. Various additional factors  affecting academic performance [such as gender, prior studies of  accounting, and computer systems, together with entry background] are incorporated in the development of a multiple regression model, together with perceptions of CAL. The study uses a sample of 280 second-year undergraduate accounting students from an Australian university to test the model. In contrast to prior studies (e.g. Lane and Porch, 2002, Accounting Education: an international journal, 11(3), pp. 217-233), this study showed that positive perceptions of the usefulness of CAL significantly influenced performance. Additionally, it was found that international students, many of whom enter university at the second year level having obtained advanced standing credits, had significantly poorer performance than local students. The findings show that gender, prior studies of accounting and computing systems were not significant influences on academic performance. Overall, the results have implications for accounting educators utilising CAL in courses as a means of improving students' understanding of accounting concepts and academic performance.

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This study examines the factors affecting student performance in an undergraduate financial accounting course, utilising Computer Assisted Learning (CAL) and use of a commercial software package. Multiple regression analysis was undertaken to examine the influences of perceptions of CAL and QuickBooks Pro, together with background variables such as gender, entry pathway and prior knowledge had on student performance. The results show that perceptions of CAL together with entry pathway were significant predictors of student performance. However, perceptions of the ,usefulness of QuickBooks Pro, prior studies of accounting and computing, together with gender, were not significant influences on performance. In terms of entry pathway it was found that International students, many of whom entered the university at the second year level having obtained advanced standing credits, had significantly poorer performance than local students. This result may be attributed to transitional problems experienced by these students, given their different pathways to university study.

The results have implications for accounting educators utilising CAL in courses as a means of improving students understanding of accounting concepts. The study also provides reflections on the use of CAL and a commercial software package as a means of providing efficient and effective educational instruction to maximise learning outcomes in accounting.

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The goal of this research is to develop a computer aided diagnostic (CAD) system that can detect breast cancer in the early stage by using microarray and image data. We verified the performance of six well known classification algorithms with various performance matrices. Although we do not suggest a unique classifier algorithm for a CAD system, we do identify a number of algorithms whose performance is very promising. The algorithms performance was validated by 3 images dataset; two have been used for the first time in this experiment. Multidimensional image filtering is adopted for the final data extraction. The image data classification performance is compared with microarray data. Results suggest the most effective means of breast cancer identification in the early stage is a hybrid approach.

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The level of satisfaction of computer-assisted tutorial courseware that is used as part of the undergraduate property and construction course at the University of Melbourne. It is important to determine if the computer-assisted teaching model improves the learning experience for students. This research examines the levels of satisfaction with a courseware model for teaching construction cost planning. The conclusions suggest that the advantages of the use of the model must be identified and actively supported throughout the whole course. In addition, further development of computer-based courseware is pointless unless the problems associated with their use can be minimized.

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This paper justifies the presentation of a Phd thesis about Computer Assisted NdjTbbana on a Digital Video Disc (DVD). NdjTbbana is a language spoken by 200 Kunibfdji who are the traditional indigenous Australian landowners of Maningrida in Arnhem Land, Australia. The tools of this study are simple digital talking books that were created in NdjTbbana and then presented on touch screens computers. The data was the interaction around the touch screens that was recorded on digital video. Using DVD technology, the NdjTbbana talking books and the digital video can be integrated into a scholarly text for academics and NdjTbbana narrated report for the Kunibfdji, which can be combined to present a thesis. From a theoretical perspective, a thesis on a DVD can be located in the centre of critical literacy, a critical theory of technology and critical research methodologies. There are also logistical, semiotic and ideological reasons for presenting a thesis on about computer assisted NdjTbbana on DVD. Presenting Computer Assisted NdjTbbana on DVD will link the tools and data of the research with academic discourse to enhance the examination process and will also support the empowerment of the Kunibfdji as they are more informed about the research process.

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Researchers strive to optimize data quality in order to ensure that study findings are valid and reliable. In this paper, we describe a data quality control program designed to maximize quality of survey data collected using computer-assisted personal interviews. The quality control program comprised three phases: (1) software development, (2) an interviewer quality control protocol, and (3) a data cleaning and processing protocol. To illustrate the value of the program, we assess its use in the Translating Research in Elder Care Study. We utilize data collected annually for two years from computer-assisted personal interviews with 3004 healthcare aides. Data quality was assessed using both survey and process data. Missing data and data errors were minimal. Mean and median values and standard deviations were within acceptable limits. Process data indicated that in only 3.4% and 4.0% of cases was the interviewer unable to conduct interviews in accordance with the details of the program. Interviewers’ perceptions of interview quality also significantly improved between Years 1 and 2. While this data quality control program was demanding in terms of time and resources, we found that the benefits clearly outweighed the effort required to achieve high-quality data.

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Data mining refers to extracting or "mining" knowledge from large amounts of data. It is an increasingly popular field that uses statistical, visualization, machine learning, and other data manipulation and knowledge extraction techniques aimed at gaining an insight into the relationships and patterns hidden in the data. Availability of digital data within picture archiving and communication systems raises a possibility of health care and research enhancement associated with manipulation, processing and handling of data by computers.That is the basis for computer-assisted radiology development. Further development of computer-assisted radiology is associated with the use of new intelligent capabilities such as multimedia support and data mining in order to discover the relevant knowledge for diagnosis. It is very useful if results of data mining can be communicated to humans in an understandable way. In this paper, we present our work on data mining in medical image archiving systems. We investigate the use of a very efficient data mining technique, a decision tree, in order to learn the knowledge for computer-assisted image analysis. We apply our method to the classification of x-ray images for lung cancer diagnosis. The proposed technique is based on an inductive decision tree learning algorithm that has low complexity with high transparency and accuracy. The results show that the proposed algorithm is robust, accurate, fast, and it produces a comprehensible structure, summarizing the knowledge it induces.

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The outcome of this research is a hybrid system called Image Indexing for Mobile Phone (ID4MP). It was developed based on a new hybrid algorithm called Ferial's Hybrids Algorithm (FHSA). The system has a good feature of efficiency, accuracy and performance in retrieving and delivering learning content to students' mobile phones.

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An Interactive electronic Atlas (IeA) was developed to assist first-year nursing students with interpretation of laboratory-based prosected cadaveric material. It was designed, using pedagogically sound principles, as a student-centered resource accessible to students from a wide range of learning backgrounds. It consisted of a highly simplified interactive interface limited to essential anatomical structures and was intended for use in a blended learning situation. The IeA's nine modules mirrored the body systems covered in a Nursing Biosciences course, with each module comprising a maximum of 10 pages using the same template: an image displaying a cadaveric specimen and, in most cases, a corresponding anatomical model with navigation panes (menus) on one side. Cursor movement over the image or clicking the menu highlighted the structure with a transparent overlay and revealed a succinct functional description. The atlas was complemented by a multiple-choice database of nearly 1,000 questions using IeA images. Students' perceptions of usability and utility were measured by survey (n = 115; 57% of the class) revealing mean access of 2.3 times per week during the 12-week semester and a median time of three hours of use. Ratings for usability and utility were high, with means ranging between 4.24 and 4.54 (five-point Likert scale; 5 = strongly agree). Written responses told a similar story for both usability and utility. The role of providing basic computer-assisted learning support for a large first-year class is discussed in the context of current research into student-centered resources and blended learning in human anatomy.