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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Modern methods in the prevention and management of complications in labor

Ojala, K. (Kati) 27 April 2010 (has links)
Abstract Although in Finland the incidence of maternal and neonatal mortality in labor is very low, labor carries some risks. This study focused on two major complications in labor: fetal asphyxia and maternal hemorrhage. The roles of fetal electrocardiographic ST-analysis (STAN) and pelvic artery embolization in the prevention and management of these complications were investigated. Intrapartum fetal monitoring aims at a timely detection of fetal hypoxemia. When non-selected parturients were randomly assigned to be monitored during labor either by STAN or conventional cardiotocography, no differences between the groups were detected in terms of neonatal outcome and operative delivery rates. Only the incidence of fetal blood sampling was lower in the STAN group. In the interpretation of the STAN tracings according to the guideline matrix provided by the STAN manufacturer, the interobserver agreement was moderate; in terms of clinical decision -making as to whether to intervene in the labor, this agreement varied from moderate to good among STAN-trained obstetricians. The aim of prophylactic pelvic artery occlusion balloon catheterization, with or without embolization, is to reduce hemorrhage in elective cesarean operations in patients with placenta accreta. Furthermore, pelvic arterial embolization may be performed post partum if bleeding continues after cesarean hysterectomy, or may serve as an alternative to hysterectomy. In the present study, pelvic artery catheterization and embolization did not reduce blood loss during cesarean delivery, nor did it decrease the need to perform hysterectomy in patients with placenta accreta. In the management of massive postpartum hemorrhage, pelvic artery embolization was most successful in patients with uterine atony, with a success rate of 75% in achieving hemostasis. However, the angiographic method included risk of complications, the most hazardous being thromboembolic complications. To conclude, STAN does not provide improvement in intrapartum fetal monitoring when compared to cardiotocography, but the need for fetal blood sampling is reduced. This may relate to the fact that subjective interpretation of STAN data is moderate at best. Prophylactic catheterization and embolization of pelvic arteries does not improve the surgical outcome of patients with placenta accreta. In the management of postpartum hemorrhage, pelvic artery embolization should be considered, especially in cases with uterine atony.
2

Reliability of Treatment Integrity Assessment with Multiple Observers: Can Agreement Be Assumed?

Cohen, Lindsay Anne 05 1900 (has links)
Interobserver agreement (IOA) was calculated across three participant dyads for a generalized treatment integrity tool. No dyads achieved 80% agreement during baseline. Task clarification was piloted as an intervention for two of the three dyads. Form agreement produced stabilization in both dyads and improvement in one dyad. Time agreement did not improve but demonstrated marked trends in one dyad.
3

Übereinstimmung in der Beurteilung zwischen Pneumologen und dem Zytopathologen, die identisches Pleuraergussmaterial untersucht haben / -

Pietrzak, Sebastian 27 October 2106 (has links)
No description available.
4

Caracterização de lesões em imagens digitais de ultrassonografia e elastografia da mama utilizando técnicas inteligentes / Characterization of lesions in ultrasound and elastography images using machine learning methods

Marcomini, Karem Daiane 30 October 2017 (has links)
Muitos procedimentos vêm sendo desenvolvidos para auxiliar no diagnóstico precoce do câncer de mama. Devido a subjetividade na interpretação de imagens, os sistemas de diagnóstico auxiliado por computador (CADx) têm oferecido ao especialista uma segunda opinião mais precisa e confiável. Nesse propósito, essa pesquisa apresenta uma metodologia de investigação da potencialidade diagnóstica de um sistema computacional na classificação de achados suspeitos em imagens de ultrassom modo-B e de elastografia da mama. A base de dados foi constituída por 31 lesões malignas e 52 benignas e um conjunto adicional contendo 206 lesões de ultrassom modo-B (144 benignas e 62 malignas) para a realização dos testes de aprendizado de máquina. O contorno foi determinado automaticamente e através do delineamento manual de três radiologistas sob a imagem de ultrassom modo-B e, em seguida, mapeado na imagem elastográfica. As lesões foram classificadas pelo sistema CADx desenvolvido para ultrassom modo-B e elastografia do tipo strain. Os dados foram avaliados por meio da sensibilidade, especificidade e AUC. O sistema CADx desenvolvido proporcionou equivalência diagnóstica para a classificação das lesões a partir das diversas formas de determinação do contorno (manual e automática), permitindo a redução da variabilidade. Além disso, o sistema apontou resultados superiores à análise visual do radiologista que, quando considerado o resultado fornecido pela associação entre as imagens de ultrassom modo-B e elastografia, proporcionou um aumento comparativo de cerca de 7% em sensibilidade e 17,2% em especificidade nos testes com o sistema CADx usando o contorno feito pelo radiologista mais experiente. Além disso, constatou-se uma influência positiva no uso da ferramenta computacional pelos radiologistas, pois, na média, seus índices de sensibilidade e especificidade diagnóstica aumentaram também em relação à situação de análise convencional, passando de 87,1% e 55,8% para 90,3% e 73,1%, respectivamente. / Many procedures have been developed to aid in the early detection and diagnosis of breast cancer. In this context, Computer-Aided Diagnosis (CADx) systems were designed to provide to the specialist a reliable second opinion. This study presents the proposal of investigating the diagnostic ability of a computational system in the characterization of suspicious findings in B-mode ultrasound and breast elastography imaging. The database consisted of 31 malignant and 52 benign lesions and an additional data set containing 206 lesions (144 benign and 62 malignant) seen only on the B-mode ultrasound for performing the machine learning tests. Three radiologists drew manually the contour of the lesions in B-mode ultrasound and we used an automatic technique to segment the lesions. Then, the contour was mapped in the elastography image. The lesions were classified using the CADx system developed for B-mode ultrasound and strain elastography. We calculated the sensitivity, specificity and AUC to evaluate the data. The developed CADx system provided a diagnostic concordance in the classification of breast lesions from the different ways of contour determination (manual and automatic), allowing to reduce the diagnostic variability. In addition, the CADx system showed superior results to the visual analysis of the radiologist. When the radiologist associated both examinations (B-mode ultrasound and elastography), his visual analysis provided 87.10%, 55.77% and 0.714 of sensitivity, specificity and AUC, respectively. When we considered the result provided by the association between B-mode ultrasound and elastography images, the CADx system provided a comparative increase of about 7% of sensitivity and 17.2% of specificity, using the contour delimited by the most experienced radiologist. In addition, a positive influence was observed in the use of the computational tool by radiologists, since, on average, their sensitivity and specificity indexes also increased in relation to the conventional analysis, from 87.1% and 55.8% to 90.3% and 73.1%, respectively.
5

Caracterização de lesões em imagens digitais de ultrassonografia e elastografia da mama utilizando técnicas inteligentes / Characterization of lesions in ultrasound and elastography images using machine learning methods

Karem Daiane Marcomini 30 October 2017 (has links)
Muitos procedimentos vêm sendo desenvolvidos para auxiliar no diagnóstico precoce do câncer de mama. Devido a subjetividade na interpretação de imagens, os sistemas de diagnóstico auxiliado por computador (CADx) têm oferecido ao especialista uma segunda opinião mais precisa e confiável. Nesse propósito, essa pesquisa apresenta uma metodologia de investigação da potencialidade diagnóstica de um sistema computacional na classificação de achados suspeitos em imagens de ultrassom modo-B e de elastografia da mama. A base de dados foi constituída por 31 lesões malignas e 52 benignas e um conjunto adicional contendo 206 lesões de ultrassom modo-B (144 benignas e 62 malignas) para a realização dos testes de aprendizado de máquina. O contorno foi determinado automaticamente e através do delineamento manual de três radiologistas sob a imagem de ultrassom modo-B e, em seguida, mapeado na imagem elastográfica. As lesões foram classificadas pelo sistema CADx desenvolvido para ultrassom modo-B e elastografia do tipo strain. Os dados foram avaliados por meio da sensibilidade, especificidade e AUC. O sistema CADx desenvolvido proporcionou equivalência diagnóstica para a classificação das lesões a partir das diversas formas de determinação do contorno (manual e automática), permitindo a redução da variabilidade. Além disso, o sistema apontou resultados superiores à análise visual do radiologista que, quando considerado o resultado fornecido pela associação entre as imagens de ultrassom modo-B e elastografia, proporcionou um aumento comparativo de cerca de 7% em sensibilidade e 17,2% em especificidade nos testes com o sistema CADx usando o contorno feito pelo radiologista mais experiente. Além disso, constatou-se uma influência positiva no uso da ferramenta computacional pelos radiologistas, pois, na média, seus índices de sensibilidade e especificidade diagnóstica aumentaram também em relação à situação de análise convencional, passando de 87,1% e 55,8% para 90,3% e 73,1%, respectivamente. / Many procedures have been developed to aid in the early detection and diagnosis of breast cancer. In this context, Computer-Aided Diagnosis (CADx) systems were designed to provide to the specialist a reliable second opinion. This study presents the proposal of investigating the diagnostic ability of a computational system in the characterization of suspicious findings in B-mode ultrasound and breast elastography imaging. The database consisted of 31 malignant and 52 benign lesions and an additional data set containing 206 lesions (144 benign and 62 malignant) seen only on the B-mode ultrasound for performing the machine learning tests. Three radiologists drew manually the contour of the lesions in B-mode ultrasound and we used an automatic technique to segment the lesions. Then, the contour was mapped in the elastography image. The lesions were classified using the CADx system developed for B-mode ultrasound and strain elastography. We calculated the sensitivity, specificity and AUC to evaluate the data. The developed CADx system provided a diagnostic concordance in the classification of breast lesions from the different ways of contour determination (manual and automatic), allowing to reduce the diagnostic variability. In addition, the CADx system showed superior results to the visual analysis of the radiologist. When the radiologist associated both examinations (B-mode ultrasound and elastography), his visual analysis provided 87.10%, 55.77% and 0.714 of sensitivity, specificity and AUC, respectively. When we considered the result provided by the association between B-mode ultrasound and elastography images, the CADx system provided a comparative increase of about 7% of sensitivity and 17.2% of specificity, using the contour delimited by the most experienced radiologist. In addition, a positive influence was observed in the use of the computational tool by radiologists, since, on average, their sensitivity and specificity indexes also increased in relation to the conventional analysis, from 87.1% and 55.8% to 90.3% and 73.1%, respectively.
6

The Development of a Three Minute Realtime Sampling Method to Measure Social Harmony during Interactions between Parents and their Toddlers with Autism

Cunningham, Isabel L. 08 1900 (has links)
Training parents of a child with autism to increase the frequency of their child's social behavior may improve the quality of parent-child interactions. The purpose of this methodological study was to develop a direct observation method for rapidly sampling social harmony between parents and their toddlers with autism during parent training interactions. The current study used a pre and post probe design, with benchmark comparisons to test the discriminability of the measurement protocol across two sets of data. The first set of data came from pre and post training videos from a parent training program for children with a diagnosis of autism or at risk for a diagnosis. The second set of data came from videos of typically developing toddlers and their parents. The results of the study show that the measurement system differentiated in the level of harmonious engagement between the benchmark sample and the sample including children diagnosed with autism. The results are discussed in the context of future directions and the utility of the measurement system for behavior analytic practices in parent training and other settings where rapport and complex interactional behaviors are an intervention priority.

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