Técnicas de análise de imagens para detecção de retinopatia diabética

Orientadores: Anderson de Rezende Rocha. Jacques WainerTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Retinopatia Diabética (RD) é uma complicação a longo prazo do diabetes e a principal causa de cegueira da população ativa. Consultas regulares são necessárias para diagnosticar a retinopatia em um estágio inicial, permitindo um tratamento com o melhor prognóstico capaz de retardar ou até mesmo impedir a cegueira. Alavancados pela evolução da prevalência do diabetes e pelo maior risco que os diabéticos têm de desenvolver doenças nos olhos, diversos trabalhos com abordagens bem estabelecidas e promissoras vêm sendo desenvolvidos para triagem automática de retinopatia. Entretanto, a maior parte dos trabalhos está focada na detecção de lesões utilizando características visuais particulares de cada tipo de lesão. Além do mais, soluções artesanais para avaliação de necessidade de consulta e de identificação de estágios da retinopatia ainda dependem bastante das lesões, cujo repetitivo procedimento de detecção é complexo e inconveniente, mesmo se um esquema unificado for adotado. O estado da arte para avaliação automatizada de necessidade de consulta é composto por abordagens que propõem uma representação altamente abstrata obtida inteiramente por meio dos dados. Usualmente, estas abordagens recebem uma imagem e produzem uma resposta ¿ que pode ser resultante de um único modelo ou de uma combinação ¿ e não são facilmente explicáveis. Este trabalho objetivou melhorar a detecção de lesões e reforçar decisões relacionadas à necessidade de consulta, fazendo uso de avançadas representações de imagens em duas etapas. Nós também almejamos compor um modelo sofisticado e direcionado pelos dados para triagem de retinopatia, bem como incorporar aprendizado supervisionado de características com representação orientada por mapa de calor, resultando em uma abordagem robusta e ainda responsável para triagem automatizada. Finalmente, tivemos como objetivo a integração das soluções em dispositivos portáteis de captura de imagens de retina. Para detecção de lesões, propusemos abordagens de caracterização de imagens que possibilitem uma detecção eficaz de diferentes tipos de lesões. Nossos principais avanços estão centrados na modelagem de uma nova técnica de codificação para imagens de retina, bem como na preservação de informações no processo de pooling ou agregação das características obtidas. Decidir automaticamente pela necessidade de encaminhamento do paciente a um especialista é uma investigação ainda mais difícil e muito debatida. Nós criamos um método mais simples e robusto para decisões de necessidade de consulta, e que não depende da detecção de lesões. Também propusemos um modelo direcionado pelos dados que melhora significativamente o desempenho na tarefa de triagem da RD. O modelo produz uma resposta confiável com base em respostas (locais e globais), bem como um mapa de ativação que permite uma compreensão de importância de cada pixel para a decisão. Exploramos a metodologia de explicabilidade para criar um descritor local codificado em uma rica representação em nível médio. Os modelos direcionados pelos dados são o estado da arte para triagem de retinopatia diabética. Entretanto, mapas de ativação são essenciais para interpretar o aprendizado em termos de importância de cada pixel e para reforçar pequenas características discriminativas que têm potencial de melhorar o diagnósticoAbstract: Diabetic Retinopathy (DR) is a long-term complication of diabetes and the leading cause of blindness among working-age adults. A regular eye examination is necessary to diagnose DR at an early stage, when it can be treated with the best prognosis and the visual loss delayed or deferred. Leveraged by the continuous expansion of diabetics and by the increased risk that those people have to develop eye diseases, several works with well-established and promising approaches have been proposed for automatic screening. Therefore, most existing art focuses on lesion detection using visual characteristics specific to each type of lesion. Additionally, handcrafted solutions for referable diabetic retinopathy detection and DR stages identification still depend too much on the lesions, whose repetitive detection is complex and cumbersome to implement, even when adopting a unified detection scheme. Current art for automated referral assessment resides on highly abstract data-driven approaches. Usually, those approaches receive an image and spit the response out ¿ that might be resulting from only one model or ensembles ¿ and are not easily explainable. Hence, this work aims at enhancing lesion detection and reinforcing referral decisions with advanced handcrafted two-tiered image representations. We also intended to compose sophisticated data-driven models for referable DR detection and incorporate supervised learning of features with saliency-oriented mid-level image representations to come up with a robust yet accountable automated screening approach. Ultimately, we aimed at integrating our software solutions with simple retinal imaging devices. In the lesion detection task, we proposed advanced handcrafted image characterization approaches to detecting effectively different lesions. Our leading advances are centered on designing a novel coding technique for retinal images and preserving information in the pooling process. Automatically deciding on whether or not the patient should be referred to the ophthalmic specialist is a more difficult, and still hotly debated research aim. We designed a simple and robust method for referral decisions that does not rely upon lesion detection stages. We also proposed a novel and effective data-driven model that significantly improves the performance for DR screening. Our accountable data-driven model produces a reliable (local- and global-) response along with a heatmap/saliency map that enables pixel-based importance comprehension. We explored this methodology to create a local descriptor that is encoded into a rich mid-level representation. Data-driven methods are the state of the art for diabetic retinopathy screening. However, saliency maps are essential not only to interpret the learning in terms of pixel importance but also to reinforce small discriminative characteristics that have the potential to enhance the diagnosticDoutoradoCiência da ComputaçãoDoutor em Ciência da ComputaçãoCAPE

Knowledge Transfer for Melanoma Screening with Deep Learning

Knowledge transfer impacts the performance of deep learning -- the state of the art for image classification tasks, including automated melanoma screening. Deep learning's greed for large amounts of training data poses a challenge for medical tasks, which we can alleviate by recycling knowledge from models trained on different tasks, in a scheme called transfer learning. Although much of the best art on automated melanoma screening employs some form of transfer learning, a systematic evaluation was missing. Here we investigate the presence of transfer, from which task the transfer is sourced, and the application of fine tuning (i.e., retraining of the deep learning model after transfer). We also test the impact of picking deeper (and more expensive) models. Our results favor deeper models, pre-trained over ImageNet, with fine-tuning, reaching an AUC of 80.7% and 84.5% for the two skin-lesion datasets evaluated.Comment: 4 page

Optimized Adaptive Streaming Representations based on System Dynamics

Adaptive streaming addresses the increasing and heterogenous demand of multimedia content over the Internet by offering several encoded versions for each video sequence. Each version (or representation) has a different resolution and bit rate, aimed at a specific set of users, like TV or mobile phone clients. While most existing works on adaptive streaming deal with effective playout-control strategies at the client side, we take in this paper a providers' perspective and propose solutions to improve user satisfaction by optimizing the encoding rates of the video sequences. We formulate an integer linear program that maximizes users' average satisfaction, taking into account the network dynamics, the video content information, and the user population characteristics. The solution of the optimization is a set of encoding parameters that permit to create different streams to robustly satisfy users' requests over time. We simulate multiple adaptive streaming sessions characterized by realistic network connections models, where the proposed solution outperforms commonly used vendor recommendations, in terms of user satisfaction but also in terms of fairness and outage probability. The simulation results further show that video content information as well as network constraints and users' statistics play a crucial role in selecting proper encoding parameters to provide fairness a mong users and to reduce network resource usage. We finally propose a few practical guidelines that can be used to choose the encoding parameters based on the user base characteristics, the network capacity and the type of video content

Sabi\'a: Portuguese Large Language Models

As the capabilities of language models continue to advance, it is conceivable that "one-size-fits-all" model will remain as the main paradigm. For instance, given the vast number of languages worldwide, many of which are low-resource, the prevalent practice is to pretrain a single model on multiple languages. In this paper, we add to the growing body of evidence that challenges this practice, demonstrating that monolingual pretraining on the target language significantly improves models already extensively trained on diverse corpora. More specifically, we further pretrain GPT-J and LLaMA models on Portuguese texts using 3% or less of their original pretraining budget. Few-shot evaluations on Poeta, a suite of 14 Portuguese datasets, reveal that our models outperform English-centric and multilingual counterparts by a significant margin. Our best model, Sabi\'a-65B, performs on par with GPT-3.5-turbo. By evaluating on datasets originally conceived in the target language as well as translated ones, we study the contributions of language-specific pretraining in terms of 1) capturing linguistic nuances and structures inherent to the target language, and 2) enriching the model's knowledge about a domain or culture. Our results indicate that the majority of the benefits stem from the domain-specific knowledge acquired through monolingual pretraining

Mídia e educação física escolar no meio rural de Sombrio/SC

Trabalho de Conclusão de Curso, apresentado para obtenção do grau de Lienciatura no curso de Educação Física da Universidade do Extremo Sul Catarinense, UNESC.A pesquisa tem como objetivo principal analisar até que ponto a mídia influencia os alunos nas aulas de Educação Física na zona rural em Sombrio/SC. A partir de uma pesquisa de campo, tendo como procedimento metodológico observação das aulas de Educação Física e entrevista aplicada com alunos do 3º ao 5º ano de uma escola rural de Sombrio-SC. Segundo as análises desta pesquisa os alunos tem acesso à mídia, porém não é tratada como prioridade, influenciando minimamente nas aulas. Esse acesso limitado à mídia leva à falta de informação com relação à contemporaneidade da cultura corporal

Civilizar e modernizar: o ensino agrícola no Brasil republicano (1889-1930)

 O trabalho enfoca a constituição de uma rede social de projetos, abrangendo o território nacional, na qual foram incorporadas as representações e ações sociais produzidas, materializadas e transmitidas pelo Ministério da Agricultura, Indústria e Comércio do Brasil, as quais tomaram como tema central as condições sociais no campo. As intervenções eram orientadas para uma modernização, concebida a partir da introdução de princípios científicos nas atividades agropecuárias. Progresso e civilização eram faces de um pretendido Brasil moderno. A constituição e articulação do ensino e pesquisa foram centradas num sistema educacional, abrangendo desde cursos elementares até superior. A análise está centrada no período da 1ª República no Brasil (1889-1930), delineando a diversidade das propostas incorporadas no que poderia ser denominada de uma pedagogia para o campo, a qual foi configurada junto ao governo federal. Foram consultados os relatórios anuais dos ministérios, que eram endereçados ao Presidente da República.Palavras-chave: instituições educacionais, ensino agrícola, Estado.   Abstract This paper focalizes the constitution of a social set of nationwide social projects, indeed a large net of projects, which incorporated the social representations and actions produced, materialized and transmitted by the Brazilian Agricultural, Industry and Commerce Ministry. Main themes were the social conditions on the hinterland. Its interventions were oriented onto a modernization, concerned to the introduction of scientific principies on the agricultural activities. Progress and civilization were the faces of an intended modernized Brazil. The constitution and articulation between teaching and research were centralized on an educational system, offering since elementary until graduate courses. This analysis focalizes the First Republic in Brazil (1889-1930), highlighting the diversity of the incorporated proposals, in a pedagogy for the hinterland, created by the federal government. We consulted the annual proceedings from the ministries, addressed to the republic's president. Keywords: educational institutions, agricultural teaching, State.

Effects of Drop-Set and Pyramidal Resistance Training Systems on Microvascular Oxygenation: A Near-Infrared Spectroscopy Approach

International Journal of Exercise Science 13(2): 1549-1562, 2020. Metabolic stress is a primary mechanism of muscle hypertrophy and is associated with microvascular oxygenation and muscle activation. Considering that drop-set (DS) and crescent pyramid (CP) resistance training systems are recommended to modulate these mechanisms related to muscle hypertrophy, we aimed to investigate if these resistance training systems produce a different microvascular oxygenation status and muscle activation from those observed in traditional resistance training (TRAD). Twelve volunteers had their legs randomized in an intra-subject cross-over design in TRAD (3 sets of 10 repetitions at 75% 1-RM), DS (3 sets of ~50-75% 1-RM) and CP (3 sets of 6-10 repetitions at 75-85% 1-RM). Vastus medialis microvascular oxygenation and muscle activation were respectively assessed by non- invasive near-infrared spectroscopy and surface electromyography techniques during the resistance training sessions in the leg-extension exercise. Total hemoglobin area under the curve (AUC) (TRAD: -1653.5 ± 2866.5; DS: -3069.2 ± 3429.4; CP: -1196.6 ± 2675.3) and tissue oxygen saturation (TRAD: 19283.1 ± 6698.0; DS: 23995.5 ± 15604.9; CP: 16109.1 ± 8553.1) increased without differences between protocols (p\u3e0.05). Greater decreases in oxygenated hemoglobin AUC and hemoglobin differentiated AUC were respectively found for DS (-4036.8 ± 2698.1; -5004.4 ± 2722.9) compared with TRAD (-1951.8 ± 1720.0; -2250.3 ± 1305.7) and CP (-1814.4 ± 2634.3; 2432.2 ± 2891.4) (p\u3c0.03). Higher increases of hemoglobin deoxygenated AUC were found for DS (1426.7 ± 1320.7) compared with TRAD (316.0 ± 1164.9) only (p=0.04). No differences were demonstrated in electromyographic amplitudes between TRAD (69.0 ± 34.4), DS (61.3 ± 26.7) and CP (60.9 ± 38.8) (p\u3e0.05). Despite DS produced lower microvascular oxygenation levels compared with TRAD and CP, all protocols produced similar muscle activation levels

Quality of life of family caregivers of people with Down Syndrome

Objective: to analyze the perception of parents/caregivers of people with Down syndrome on quality of life. Methods: It is a qualitative study, which used for data collection semi-structured interviews with 10 caregiver parents of people with Down syndrome. To analyze the data, we used the content analysis technique. Results: It was observed that caregivers are mothers over the age of 30, who declared themselves as racially mixed (Pardo in Portuguese), live with a partner, practice some type of physical activity and attend any educational institution. Moreover, they had as main occupation the caregiver role. Caregivers reported that access to leisure; health; family relationships; general welfare; Material and rights were the factors that influence the quality of life. Conclusion: it was concluded that caregiver parents of people with Down syndrome had different views on the quality of life

Immunotherapy in patients with advanced non-small cell lung cancer lacking driver mutations and future perspectives

From a complete literature review, we were able to present in this paper what is most current in the treatment with immunotherapy for advanced non-small cell lung cancer (NSCLC). Especially the use of immunotherapy, particularly inhibitors of PD-1 (programmed cell death protein 1), PDL-1 (programmed cell death protein ligand 1), and CTLA-4 (cytotoxic T-lymphocyte antigen 4). Since 2015, these drugs have transformed the treatment of advanced NSCLC lacking driver mutations, evolving from second-line therapy to first-line, with excellent results. The arrival of new checkpoint inhibitors such as cemiplimab and the use of checkpoint inhibitors earlier in the therapy of advanced and metastatic cancers has been making the future prospects for treating NSCLC lacking driver mutations more favorable and optimistic. In addition, for those patients who have low PDL-1 positivity tumors, the combination of cytotoxic chemotherapy, VEGF inhibitor, and immunotherapy have shown an important improvement in global survival and progression free survival regardless the PDL-1 status. We also explored the effectiveness of adding radiotherapy to immunotherapy and the most current results about this combination. One concern that cannot be overlooked is the safety profile of immune checkpoint inhibitors (ICI) and the most common toxicities are described throughout this paper as well as tumor resistance to ICI.info:eu-repo/semantics/publishedVersio