O foco central desta tese consiste em procurar compreender um fenômeno que se verifica na atualidade em torno das imagens ultra-sonográficas fetais. O que era a princípio e em princípio uma tecnologia de imagem médica, inventada com propósitos diagnósticos, gradualmente transformou-se em objeto de consumo e lazer. Para investigar o fenômeno, a pesquisa teórica aborda como foram construídos o olhar e o observador modernos, e de que modo as tecnologias de imageamento médico incidem na construção social do corpo. Outro aspecto teórico consiste na investigação, de um ponto de vista sócio-histórico, acerca da produção da gravidez e do feto como temas médicos, e de que modo a tecnologia de ultra-som aplicada à obstetrícia está situada na articulação de vários processos: o da construção de um novo olhar, o das reconfigurações do corpo, o da medicalização da gestação e do feto e, finalmente, o da construção do feto como Pessoa antes de seu nascimento. Estudos antropológicos produzidos no exterior, ao longo da década de 1990, apontaram que o fenômeno envolvendo as imagens fetais encontrava-se inscrito nos e delimitado pelos códigos socioculturais específicos de onde ocorriam. A inexistência de pesquisas acerca do tema, no contexto brasileiro, foi o ponto de partida para uma investigação empírica. Foi realizada uma observação antropológica de ultra-sonografias obstétricas, em abordagem etnográfica, em três clínicas privadas de imagem, ao longo de 2003, no Rio de Janeiro, visando compreender como tal fenômeno se dava, de que modo era produzido e significado pelos atores e quais os desdobramentos de tais práticas, modelados por especificidades culturais locais. O trabalho de campo evidenciou que a ultra-sonografia obstétrica caracteriza-se por ser uma tecnologia de imagem interativa, em contraste com outras técnicas de imageamento médico, uma peculiaridade que propicia a construção de diversos significados a partir das imagens fetais cinzentas e esfumaçadas. A produção do prazer de ver o feto é a pedra de toque que une o útil ao agradável, e o consumo de imagens é um ponto de articulação de diversas questões expostas ao longo da tese. Pode-se pensar nesta situação como parte de um panopticismo que devassa corpos femininos e fetais, em um mesmo processo normatizando-os e construindo novos sujeitos calcados em corporalidades virtuais. / The central focus of this thesis consists of seeking to understand a phenomenon which is presently taking place in the area of fetal ultrasound images. What began as a medical imaging technology, invented for diagnostic purposes, gradually became an object of consumption and leisure. In order to investigate this phenomenon, the theoretical investigation looks at how the modern mode of seeing and the observer were constructed, and in what way technologies of medical imaging impact the social construction of the body. Another theoretical aspect consists of the investigation, from a socio-historical point of view, of the production of pregnancy and of the fetus as medical subjects, and in what way the technology of ultra-sound applied to obstetrics is situated at the nexus of various processes: the process of constructing a new mode of seeing, of the reconfigurations of the body, of the medicalization of gestation and of the fetus, and, finally, of the construction of the fetus as a person before its birth. Anthropological studies carried out abroad, during the nineties, show that the phenomenon involving fetal images was inscribed in and delimited by the specific socio-cultural codes where the imaging was done. The lack of research in this area in the Brazilian context was the point of departure for an empirical investigation. An anthropological observation of obstetric ultra-sounds, with an ethnographic approach, was carried out in three private imaging clinics, during the course of 2003, in Rio de Janeiro, with the intention of understanding how this phenomenon took place, in what way it was produced and signified by those involved, and what were the ramifications of these practices, modeled by local cultural particularities. The field work showed that obstetric ultrasonography can be characterized as an interactive imaging technique, in contrast to other medical imaging techniques, a peculiarity which lends itself to the construction of various significations having as their origin gray and hazy fetal images. The production of the pleasure of seeing the fetus is the touchstone which links the useful to the pleasing, and the consumption of images is point of connection for various questions raised in the thesis. One can think of this situation as part of a panopticism which scans female and fetal bodies, at one and the same time normatizing them and constructing new subjects shaped by virtual corporalities.

The text deals with ways and methods of creating my diploma thesis called Steal me your €motion. The diploma thesis deals with the relationship between machine learning and emotionality. To what extent is artificial intelligence able to undergo emotional relationships and experiences defined by the physicality and experience of the human body. The topic of the work is the creation of a (fictional) inhuman entity that longs to learn from people as many bodily acts as possible that will help it infiltrate the human community. In addition to reflecting the current level of scientific knowledge, I bring an element of fiction and fiction.

This study explores the potential of artificial intelligence (AI) in enhancing the diagnosis of brain tumours, specifically through a comparative analysis of two advanced deep learning (DL) models, ResNet50 and YOLOv8, applied to detect and classify brain tumours in MRI images. The study addresses the critical need for rapid and accurate diagnostic tools in the medical field, given the complexity and diversity of brain tumours. The research was motivated by the potential benefits AI could offer to medical diagnostics, particularly in terms of speed and accuracy, which are crucial for effective patient treatment and outcomes. The performance of the ResNet50 and YOLOv8 models was evaluated on a dataset of 7023 MRI images across four tumour types. Key metrics used were accuracy, precision, recall, specificity, F1-score, and processing time, to identify which model performs better in detecting and classifying brain tumours. The findings demonstrates that although both models exhibit high performance, YOLOv8 surpasses ResNet50 in most metrics, particularly showing advantages in speed. The findings highlight the effectiveness advanced DL models in medical image analysis, providing a significant advancement in brain tumour diagnosis. By offering a thorough comparative analysis of two commonly used DL models, aligning with ongoing approaches to integrate AI into practical medical application, and highlighting their potential uses, this study advances the area of medical AI providing insight into the knowledge required for the deployment of future AI diagnostic tools.