| 5101. |
- Moraes, Ana Luiza Dallora
(författare)
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Machine learning applications in healthcare
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Healthcare is an important and high cost sector that involves many decision-making tasks based on the analysis of data, from its primary activities up till management itself. A technology that can be useful in an environment as data-intensive as healthcare is machine learning. This thesis investigates the application of machine learning in healthcare contexts as an applied health technology (AHT). AHT refers to application of scientific methods for the development of interventions targeting practical problems related to health and healthcare.The two research contexts in this thesis regard two pivotal activities in the healthcare systems: diagnosis and prognosis. The diagnosis research context regards the age assessment of the young individuals, which aims to address the drawbacks in the bone age assessment research, investigating new age assessment methods. The prognosis research context regards the prognosis of dementia, which aims to investigate prognostic estimates for older individuals who came to develop the dementia disorder, in a time frame of 10 years. Machine learning applications were shown to be useful in both research contexts.In the diagnosis research context, study I summarized the state of the art evidence in the area of bone age assessment with the use of machine learning, identifying both automated and non-automated approaches for age assessment. Study II investigated a non-automated approach based on the radiologists' assessment and study III investigated an automated approach based on deep learning. Both studies used magnetic resonance imaging. The results showed that the radiologists' assessment as input was not precise enough for the estimation of age. However, the deep learning method was able to extract more useful features from the images and provided better diagnostic performance for the age assessment.In the research context of prognosis, study IV conducted a review on the relevant evidence in on the prognosis of dementia with machine learning techniques, identifying a focus on the research on neuroimaging studies dedicated to validating biomarkers for pharmaceutical research. Study V proposed a multifactorial decision tree approach for the prognosis of dementia in older individuals as to their development or not of dementia in 10 years. Achieving consistent performance results, it provided an interpretable prognostic model identifying possible modifiable and non-modifiable risk factors and possible patient subgroups of importance for the dementia research.
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| 5102. |
- Moraes, Ana Luiza Dallora, et al.
(författare)
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Multifactorial 10-year prior diagnosis prediction model of dementia
- 2020
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Ingår i: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 17:18, s. 1-18
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Tidskriftsartikel (refereegranskat)abstract
- Dementia is a neurodegenerative disorder that affects the older adult population. To date, no cure or treatment to change its course is available. Since changes in the brains of affected individuals could be evidenced as early as 10 years before the onset of symptoms, prognosis research should consider this time frame. This study investigates a broad decision tree multifactorial approach for the prediction of dementia, considering 75 variables regarding demographic, social, lifestyle, medical history, biochemical tests, physical examination, psychological assessment and health instruments. Previous work on dementia prognoses with machine learning did not consider a broad range of factors in a large time frame. The proposed approach investigated predictive factors for dementia and possible prognostic subgroups. This study used data from the ongoing multipurpose Swedish National Study on Aging and Care, consisting of 726 subjects (91 presented dementia diagnosis in 10 years). The proposed approach achieved an AUC of 0.745 and Recall of 0.722 for the 10-year prognosis of dementia. Most of the variables selected by the tree are related to modifiable risk factors; physical strength was important across all ages. Also, there was a lack of variables related to health instruments routinely used for the dementia diagnosis.
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| 5103. |
- Moraes, Ana Luiza Dallora, et al.
(författare)
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Nursing Students’ Attitudes Toward Technology : Multicenter Cross-Sectional Study
- 2024
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Ingår i: JMIR Medical Education. - : JMIR Publications. - 2369-3762. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Background:The growing presence of digital technologies in health care requires the health workforce to have proficiency in subjects such as informatics. This has implications in the education of nursing students, as their preparedness to use these technologies in clinical situations is something that course administrators need to consider. Thus, students’ attitudes toward technology could be investigated to assess their needs regarding this proficiency.Objective:This study aims to investigate attitudes (enthusiasm and anxiety) toward technology among nursing students and to identify factors associated with those attitudes.Methods:Nursing students at 2 universities in Sweden and 1 university in Poland were invited to answer a questionnaire. Data about attitudes (anxiety and enthusiasm) toward technology, eHealth literacy, electronic device skills, and frequency of using electronic devices and sociodemographic data were collected. Descriptive statistics were used to characterize the data. The Spearman rank correlation coefficient and Mann-Whitney U test were used for statistical inferences.Results:In total, 646 students answered the questionnaire—342 (52.9%) from the Swedish sites and 304 (47.1%) from the Polish site. It was observed that the students’ technology enthusiasm (techEnthusiasm) was on the higher end of the Technophilia instrument (score range 1-5): 3.83 (SD 0.90), 3.62 (SD 0.94), and 4.04 (SD 0.78) for the whole sample, Swedish students, and Polish students, respectively. Technology anxiety (techAnxiety) was on the midrange of the Technophilia instrument: 2.48 (SD 0.96), 2.37 (SD 1), and 2.60 (SD 0.89) for the whole sample, Swedish students, and Polish students, respectively. Regarding techEnthusiasm among the nursing students, a negative correlation with age was found for the Swedish sample (P<.001; ρSwedish=−0.201) who were generally older than the Polish sample, and positive correlations with the eHealth Literacy Scale score (P<.001; ρall=0.265; ρSwedish=0.190; ρPolish=0.352) and with the perceived skill in using computer devices (P<.001; ρall=0.360; ρSwedish=0.341; ρPolish=0.309) were found for the Swedish, Polish, and total samples. Regarding techAnxiety among the nursing students, a positive correlation with age was found in the Swedish sample (P<.001; ρSwedish=0.184), and negative correlations with eHealth Literacy Scale score (P<.001; ρall=−0.196; ρSwedish=−0.262; ρPolish=−0.133) and with the perceived skill in using computer devices (P<.001; ρall=−0.209; ρSwedish=−0.347; ρPolish=−0.134) were found for the Swedish, Polish, and total samples and with the semester only for the Swedish sample (P<.001; ρSwedish=−0.124). Gender differences were found regarding techAnxiety in the Swedish sample, with women exhibiting a higher mean score than men (2.451, SD 1.014 and 1.987, SD 0.854, respectively).Conclusions:This study highlights nursing students’ techEnthusiasm and techAnxiety, emphasizing correlations with various factors. With health care’s increasing reliance on technology, integrating health technology–related topics into education is crucial for future professionals to address health care challenges effectively.
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| 5104. |
- Moraes, Ana Louiza Dallora, et al.
(författare)
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Prognosis of dementia employing machine learning and microsimulation techniques : a systematic literature review
- 2016
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Ingår i: International Conference on ENTERprise Information Systems/International Conference on Project MANagement/International Conference on Health and Social Care Information Systems and Technologies, CENTERIS/ProjMAN / HCist 2016. - : Elsevier. ; , s. 480-488, s. 480-488
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Konferensbidrag (refereegranskat)abstract
- OBJECTIVE: The objective of this paper is to investigate the goals and variables employed in the machine learning and microsimulation studies for the prognosis of dementia. METHOD: According to preset protocols, the Pubmed, Socups and Web of Science databases were searched to find studies that matched the defined inclusion/exclusion criteria, and then its references were checked for new studies. A quality checklist assessed the selected studies, and removed the low quality ones. The remaining ones (included set) had their data extracted and summarized. RESULTS: The summary of the data of the 37 included studies showed that the most common goal of the selected studies was the prediction of the conversion from mild cognitive impairment to Alzheimer's Disease, for studies that used machine learning, and cost estimation for the microsimulation ones. About the variables, neuroimaging was the most frequent used. CONCLUSIONS: The systematic literature review showed clear trends in prognosis of dementia research in what concerns machine learning techniques and microsimulation.
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| 5105. |
- Morch, Anders, et al.
(författare)
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Component-based Technologies for End-user Development
- 2004
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Ingår i: Communications of the ACM. - New York, USA : ASSOC Computing Machinery. - 0001-0782. ; 47:9, s. 59-62
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Tidskriftsartikel (refereegranskat)abstract
- Component-based software development (CBSD) involves multiple roles. Framework builders create the infrastructure for components to interact; developers identify suitable domains and develop new components for them; application assemblers select domain-specific components and assemble them into applications; and end users employ components based applications to perform daily tasks [7].
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| 5106. |
- Moreira, André R., et al.
(författare)
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Classification of Oil Rigs in SAR Images Using RPCA-Based Preprocessing
- 2024
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Ingår i: Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR. - : Institute of Electrical and Electronics Engineers (IEEE). - 9783800762873 ; , s. 432-437
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Konferensbidrag (refereegranskat)abstract
- This paper uses a signal separation method called Robust Principal Component Analysis (RPCA) as a pre-processing technique to improve the classification of oil rigs in Synthetic Aperture Radar (SAR) images. After the pre-processing method, features are extracted from the images using the VGG-16 convolutional neural network. These features guide classification through Support Vector Machine (SVM), Neural Networks, and Logistic Regression algorithms. The experiments used SAR images from the Sentinel-1 system, C-band, and VH polarization. Early results highlight that preprocessing improves classification accuracy compared to conventional methods. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.
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| 5107. |
- Moreira, Paula S. E., et al.
(författare)
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Prime groupoid graded rings with applications to partial skew groupoid rings
- 2024
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Ingår i: Communications in Algebra. - : Taylor & Francis. - 0092-7872 .- 1532-4125. ; 52:7, s. 3134-3153
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we investigate primeness of groupoid graded rings. We provide a set of necessary and sufficient conditions for primeness of a nearly-epsilon strongly groupoid graded ring. Furthermore, we apply our main result to get a characterization of prime partial skew groupoid rings, and in particular of prime groupoid rings, thereby generalizing a classical result by Connell and partially generalizing recent results by Steinberg. © 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.
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| 5108. |
- Moss, Andrew, et al.
(författare)
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Compiler Assisted Masking
- 2012
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Ingår i: Lecture Notes in Computer Science. - Berlin, Heidelberg : Springer. ; , s. 58-75
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Konferensbidrag (refereegranskat)abstract
- Differential Power Analysis (DPA) attacks find a statistical correlation between the power consumption of a cryptographic device and intermediate values within the computation. Randomization via (Boolean) masking of intermediate values breaks this statistical dependence and thus prevents such attacks (at least up to a certain order). Especially for software implementations, (first-order) masking schemes are popular in academia and industry, albeit typically not as the sole countermeasure. The current practice then is to manually 'insert' Boolean masks: essentially software developers need to manipulate low-level assembly language to implement masking. In this paper we make a first step to automate this process, at least for first-order Boolean masking, allowing the development of compilers capable of protecting programs against DPA.
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| 5109. |
- Mostefaoui, Achour, et al.
(författare)
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Topic 8 : Distributed systems and algorithms
- 2013
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Ingår i: Lecture Notes in Computer Science. - Aachen : Springer. - 9783642400469 ; , s. 367-368
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Konferensbidrag (refereegranskat)abstract
- Distributed Computing is becoming more and more led by technological and application advances. Many works consider new computing models compared to the classical closed model with a fixed number of participants and strong hypothesis on communication and structuration. Indeed, it is hard to imagine some application or computational activity and process that falls outside Distributed Computing. Internet and the web (e.g. social networks, clouds) are becoming the main application field for distributed computing. In addition to the classical challenges that developers have to face (asynchrony and failures) they have to deal with load balancing, malicious and selfish behaviors, mobility, heterogeneity and the dynamic nature of participating processes.
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| 5110. |
- Motamediyan Dehkordi, Farnaz, et al.
(författare)
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Impacts of project-overload on innovation inside organizations : Agent-based modeling
- 2012
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Konferensbidrag (refereegranskat)abstract
- Market competition and a desire to gain advantages on globalized market, drives companies towards innovation efforts. Project overload is an unpleasant phenomenon, which is happening for employees inside those organizations trying to make the most efficient use of their resources to be innovative. But what are the impacts of project overload on organization’s innovation capabilities? Advanced engineering teams (AE) inside a major heavy equipment manufacturer are suffering from project overload in their quest for innovation. In this paper, Agent-based modeling (ABM) is used to examine the current reality of the company context, and of the AE team, where the opportunities and challenges for reducing the risk of project overload and moving towards innovation were identified. Project overload is more likely to stifle innovation and creativity inside teams. On the other hand, motivation on proper challenging goals are more likely to help individual to alleviate the negative aspects of low level of project overload
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