Evaluation of machine learning classifiers in keratoconus detection from orbscan II examinations

PURPOSE: To evaluate the performance of support vector machine, multi-layer perceptron and radial basis function neural network as auxiliary tools to identify keratoconus from Orbscan II maps. METHODS: A total of 318 maps were selected and classified into four categories: normal (n = 172), astigmatism (n = 89), keratoconus (n = 46) and photorefractive keratectomy (n = 11). For each map, 11 attributes were obtained or calculated from data provided by the Orbscan II. Ten-fold cross-validation was used to train and test the classifiers. Besides accuracy, sensitivity and specificity, receiver operating characteristic (ROC) curves for each classifier were generated, and the areas under the curves were calculated. RESULTS: The three selected classifiers provided a good performance, and there were no differences between their performances. The area under the ROC curve of the support vector machine, multi-layer perceptron and radial basis function neural network were significantly larger than those for all individual Orbscan II attributes evaluated (p<0.05). CONCLUSION: Overall, the results suggest that using a support vector machine, multi-layer perceptron classifiers and radial basis function neural network, these classifiers, trained on Orbscan II data, could represent useful techniques for keratoconus detection

Business Agglomerations: Theoretical Perceptions on the Development of Regions

Regional development is an explored topic, but it has gaps in the literature. This theoretical essay aims to examine how the approaches and distances between approaches regarding clusters can contribute to the understanding of the theme of regional development. In order to achieve the proposed objective, it was decided to present a history of the regional development, in addition to the main approaches regarding clusters. The qualitative approach proved to be relevant from the collection of bibliographic data to their. As a result, it was noticed that the theme of regional development is presented by the approaches in a complementary way and through its main causes and consequences. It was concluded that the local specificities in each of the types of clusters produce concepts that consider different demands and results for regional development

Social Capital in Bahia Clusters

This paper aimed to assess the impact of social capital on the performance of clusters in the state of Bahia Brazil Through bibliographic and documentary research it was possible to achieve the desired objective It was evident that the most developed clusters in Bahia are found in regions with good levels of social capital The operationalization of social capital results in cooperation processes that have a direct influence on the performance of the agglomerations of companies It is concluded that social capital is a decisive factor for the development of cluster

E-learning program for medical students in dermatology

INTRODUCTION: Dermatological disorders are common in medical practice. In medical school, however, the time devoted to teaching dermatology is usually very limited. Therefore, online educational systems have increasingly been used in medical education settings to enhance exposure to dermatology. OBJECTIVE: The present study was designed to develop a e-learning program for medical students in dermatology and evaluate the impact of this program on learning. METHODS: This prospective study included second year medical students at the University of Technology and Science, Salvador, Brazil. All students attended discussion seminars and practical activities, and half of the students had adjunct online seminars (blended learning). Tests were given to all students before and after the courses, and test scores were evaluated. RESULTS: Students who participated in online discussions associated with face-to-face activities (blended learning) had significantly higher posttest scores (9.0 + 0.8) than those who only participated in classes (7.75+1.8, p <0.01). CONCLUSIONS: The results indicate that an associated online course might improve the learning of medical students in dermatology

Teledermatology: diagnostic correlation in a primary care service

FUNDAMENTOS: O termo telemedicina faz referência ao uso de tecnologias de comunicação para a transmissão a distância de informações relacionadas à saúde. Esse recurso é utilizado em várias especialidades médicas, principalmente naquelas em que a interpretação de imagens representa uma etapa fundamental na formulação diagnóstica. OBJETIVO: Avaliar a concordância entre o diagnóstico presencial e o diagnóstico a distância de lesões cutâneas, utilizando a teledermatologia, em pacientes atendidos em uma unidade básica de saúde. MÉTODOS: Foi realizado um estudo prospectivo envolvendo pacientes atendidos no serviço de dermatologia da clínica FTC em Salvador - BA. Participaram do estudo um dermatologista responsável pela consulta presencial e dois dermatologistas responsáveis pela consulta a distância. Os diagnósticos obtidos através da teleconsulta foram avaliados quanto à concordância e comparados com os diagnósticos da consulta presencial. RESULTADOS: Foram incluídos neste estudo 60 pacientes. Observou-se um grau de concordância total variando de 86,6% a 91,6% com índice Kappa de 0,62. CONCLUSÃO: A teledermatologia é uma forma de assistência com um grande potencial de uso na dermatologia, podendo representar uma ferramenta útil principalmente em casos clínicos de baixa complexidade, oriundos de unidades básicas de saúde.BACKGROUND: Telemedicine can be defined as the use of telecommunication technologies for the transmission of health data. It has been described in different medical specialties, especially those in which interpretation of images represents a fundamental key in formulating diagnosis. OBJECTIVE: To evaluate the role of teledermatology in primary care system. METHODS: A prospective analysis included 60 patients seen in a primary care unit. All patients were seen by a dermatologist as regular outpatient dermatology consultation. A medical student obtained digital images and a brief clinical history of all patients. Using a Telemedicine system these data were reviewed by two dermatologists for distance diagnosis. Agreement between the diagnoses was assessed. RESULTS: Good agreement, ranging from 86.6% to 91.6%, was achieved between direct observation and teleconsultation. Good agreement was also achieved between two telemedicine diagnosis (Kappa = 0.62). CONCLUSION: Teledermatology is a form of care with great potential for use in dermatology, and could represent a useful tool in cases of low complexity from primary health units

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio