box What is already known about this subject? ► Computer-assisted systems for health image analysis have improved the medical decision-making process for diagnosing and analysing the progression of various diseases. ► Diseases affecting gastric tissue are a worldwide health problem. ► Deep learning applications presented good results in different domains, however its application on gastric tissue analysis is recent, poorly analysed, and standardised. What are the new findings? ► We provide a literature categorisation, based on the method and related tasks, identifying the most widely adopted deep learning architecture and data source used. ► This is the first systematic review dedicated to map gastric tissue deep learning applications covering a broad spectrum, also listing and evaluating open source tools. ► We identified gaps evaluation metrics, image collection availability and, consequently, implications for experimental reproducibility.How might it impact on clinical practice in the foreseeable future?► Deep learning applications can provide greater and more efficient workflow support and extraction of important information from histological images, consequently, replicable studies need to be conducted clearly, and transparently, also providing the data used.AbSTrACT background In recent years, deep learning has gained remarkable attention in medical image analysis due to its capacity to provide results comparable to specialists and, in some cases, surpass them. Despite the emergence of deep learning research on gastric tissues diseases, few intensive reviews are addressing this topic.Method We performed a systematic review related to applications of deep learning in gastric tissue disease analysis by digital histology, endoscopy and radiology images.Conclusions This review highlighted the high potential and shortcomings in deep learning research studies applied to gastric cancer, ulcer, gastritis and non-malignant diseases. Our results demonstrate the effectiveness of gastric tissue analysis by deep learning applications. Moreover, we also identified gaps of evaluation metrics, and image collection availability, therefore, impacting experimental reproducibility.
Social media plays an important role in the feminist agenda by providing a channel for denouncing and also inducing support networks. However, hate speech is conveyed in this type of media. Aiming to study this counterpoint, this paper analyzes news commentary on the feminicide attempt of the landscape artist Elaine Perez Caparroz. The approach was carried out with the collection of news and their comments, which were later analyzed using topic modeling, sentiment analysis, correlation analysis of likes and dislikes and the comments scholarly level. The results show that most of the comments share the opinion that it was the fault of Elaine Caparroz, highlighting the chauvinism that still existing in our society.Resumo. As mídias sociais têm um importante papel na agenda de lutas feministas por proporcionarem um canal de denúncia e induziremà redes de apoio. No entanto, discursos deódio também são veiculados neste tipo de mídia. Visando estudar este contraponto, o presente trabalho analisa comentários de notícias sobre a tentativa de feminicídio da paisagista Elaine Perez Caparroz. A abordagem realizada foi conduzida com a coleta de dados de notícias e seus comentários que, posteriormente, foram analisados a partir de métodos para modelagem de tópicos, análise de sentimentos, correlação com likes & dislikes e também análise do nível de escolaridade dos comentários. Os resultados mostram que a maior parte dos comentários comunga da opinião que a culpa foi de Elaine Caparroz, ressaltando o machismo que ainda há em nossa sociedade.
Resumo: Mídias digitais estão cada vez mais presentes no cotidiano do ser humano. Este fato contribui para que o volume de conteúdo gerado por usuário aumente consideravelmente. De um ponto de vista prático, as análises desses dados requerem diferentes perspectivas e métodos para se obter resultados satisfatórios. Essas análises podem subsidiar a tomada de decisão por gestores por meio da identificação de necessidades e problemas, guiando o processo de melhoria continuada de produtos e serviços. Diante disso, este trabalho propõe uma análise de reclamações postadas em uma plataforma online de reclamações, a fim de identificar pontos que orientem a tomada de decisões das empresas e, consequentemente, melhorar o relacionamento com clientes. Os resultados obtidos permitem a identificação de uma cadeia de problemas relacionados. A principal contribuição deste estudo está na provisão de uma abordagem que auxilia no planejamento estratégico de corporações, levando em consideração situações reportadas pelos consumidores.
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