Coccidioidomycosis and the skin: a comprehensive review Garcia Garcia, Sandra Cecilia; Salas Alanis, Julio Cesar; Flores, Minerva Gomez ...
Anais brasileiros de dermatología,
10/2015, Letnik:
90, Številka:
5
Journal Article
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Odprti dostop
Coccidioidomycosis is a highly prevalent disease in the Western hemisphere. It is considered one of the most virulent primary fungal infections. Coccidioides species live in arid and semi-arid ...regions, causing mainly pulmonary infection through inhalation of arthroconidia although many other organs can be affected. Primary inoculation is rare. Since the first case of coccidioidomycosis was reported in 1892, the skin has been identified as an important target of this disease. Knowledge of cutaneous clinical forms of this infection is important and very useful for establishing prompt diagnosis and treatment. The purpose of this article is to provide a review of this infection, emphasizing its cutaneous manifestations, diagnostic methods and current treatment.
In this paper, a novel strategy to perform high-dimensional feature selection using an evolutionary algorithm for the automatic classification of coronary stenosis is introduced. The method involves ...a feature extraction stage to form a bank of 473 features considering different types such as intensity, texture and shape. The feature selection task is carried out on a high-dimensional feature bank, where the search space is denoted by O(2n) and n=473. The proposed evolutionary search strategy was compared in terms of the Jaccard coefficient and accuracy classification with different state-of-the-art methods. The highest feature selection rate, along with the best classification performance, was obtained with a subset of four features, representing a 99% discrimination rate. In the last stage, the feature subset was used as input to train a support vector machine using an independent testing set. The classification of coronary stenosis cases involves a binary classification type by considering positive and negative classes. The highest classification performance was obtained with the four-feature subset in terms of accuracy (0.86) and Jaccard coefficient (0.75) metrics. In addition, a second dataset containing 2788 instances was formed from a public image database, obtaining an accuracy of 0.89 and a Jaccard Coefficient of 0.80. Finally, based on the performance achieved with the four-feature subset, they can be suitable for use in a clinical decision support system.
In this paper, a novel method for the automatic classification of coronary stenosis based on a feature selection strategy driven by a hybrid evolutionary algorithm is proposed. The main contribution ...is the characterization of the coronary stenosis anomaly based on the automatic selection of an efficient feature subset. The initial feature set consists of 49 features involving intensity, texture and morphology. Since the feature selection search space was O(2n), being n=49, it was treated as a high-dimensional combinatorial problem. For this reason, different single and hybrid evolutionary algorithms were compared, where the hybrid method based on the Boltzmann univariate marginal distribution algorithm (BUMDA) and simulated annealing (SA) achieved the best performance using a training set of X-ray coronary angiograms. Moreover, two different databases with 500 and 2700 stenosis images, respectively, were used for training and testing of the proposed method. In the experimental results, the proposed method for feature selection obtained a subset of 11 features, achieving a feature reduction rate of 77.5% and a classification accuracy of 0.96 using the training set. In the testing step, the proposed method was compared with different state-of-the-art classification methods in both databases, obtaining a classification accuracy and Jaccard coefficient of 0.90 and 0.81 in the first one, and 0.92 and 0.85 in the second one, respectively. In addition, based on the proposed method’s execution time for testing images (0.02 s per image), it can be highly suitable for use as part of a clinical decision support system.
Introduction
Metabolic and bariatric surgery (MBS) has experienced considerable growth, addressing the challenges of obesity and its complications. The lack of a comprehensive bibliometric analysis ...in Latin America motivates this study, highlighting the need to understand the evolution of research in this area and its impact on clinical decision-making and health policies.
Methodology
A cross-sectional bibliometric study was carried out using the Scopus database. A structured search strategy was designed to identify articles related to bariatric surgery with authors affiliated with Latin American countries. Inclusion and exclusion criteria were applied, followed by a descriptive and bibliometric analysis of the scientific production found.
Results
A total of 3553 documents published between 1991 and 2024 were included. There was an annual growth of 11%, with an average age of documents of 7.5 years. A concentration was observed in some countries, notably Brazil, Mexico, and Chile. Although scientific output increased, the average number of citations per article showed a downward trend since 2003.
Discussion
Despite the growth in scientific production, the quality and relevance of research is questioned, especially given the decrease in the impact received. It highlights the lack of meaningful regional collaboration, which could limit the sharing of knowledge and resources. Questions are raised about gaps in research capacity and the economic and development implications are discussed.
Conclusions
This study provides valuable information to strengthen future research in bariatric surgery in Latin America. It highlights the importance of promoting regional and international collaboration and improving research training in countries with less participation. Clinical intervention strategies can benefit from better understanding research trends and adopting evidence-based practices in a more informed manner.
Graphical Abstract
The automatic detection of coronary stenosis is a very important task in computer aided diagnosis systems in the cardiology area. The main contribution of this paper is the identification of a ...suitable subset of 20 features that allows for the classification of stenosis cases in X-ray coronary images with a high performance overcoming different state-of-the-art classification techniques including deep learning strategies. The automatic feature selection stage was driven by the Univariate Marginal Distribution Algorithm and carried out by statistical comparison between five metaheuristics in order to explore the search space, which is O(249) computational complexity. Moreover, the proposed method is compared with six state-of-the-art classification methods, probing its effectiveness in terms of the Accuracy and Jaccard Index evaluation metrics. All the experiments were performed using two X-ray image databases of coronary angiograms. The first database contains 500 instances and the second one 250 images. In the experimental results, the proposed method achieved an Accuracy rate of 0.89 and 0.88 and Jaccard Index of 0.80 and 0.79, respectively. Finally, the average computational time of the proposed method to classify stenosis cases was ≈0.02 s, which made it highly suitable to be used in clinical practice.
This paper presents a novel method for the automatic segmentation of coronary arteries in X-ray angiograms, based on multiscale analysis and neural networks. The multiscale analysis is performed by ...using Gaussian filters in the spatial domain and Gabor filters in the frequency domain, which are used as inputs by a multilayer perceptron (MLP) for the enhancement of vessel-like structures. The optimal design of the MLP is selected following a statistical comparative analysis, using a training set of 100 angiograms, and the area under the ROC curve ( A z ) for assessment of the detection performance. The detection results of the proposed method are compared with eleven state-of-the-art blood vessel enhancement methods, obtaining the highest performance of A z = 0.9775 , with a test set of 30 angiograms. The database of 130 X-ray coronary angiograms has been outlined by a specialist and approved by a medical ethics committee. On the other hand, the vessel extraction technique was selected from fourteen binary classification algorithms applied to the multiscale filter response. Finally, the proposed segmentation method is compared with twelve state-of-the-art vessel segmentation methods in terms of six binary evaluation metrics, where the proposed method provided the most accurate coronary arteries segmentation with a classification rate of 0.9698 and Dice coefficient of 0.6857 , using the test set of angiograms. In addition to the experimental results, the performance in the detection and segmentation steps of the proposed method have also shown that it can be highly suitable for systems that perform computer-aided diagnosis in X-ray imaging.
Within eye diseases, diabetic retinopathy and retinopathy of prematurity are considered one of the main causes of blindness in adults and children. In order to prevent the disease from reaching such ...an extreme, a timely diagnosis and effective treatment must be applied. Until now, the way to verify the state of the retina has been to make qualitative observations of fundus images, all carried out by an ophthalmological specialist; however, this is totally restricted to their experience, and some changes in the vascular structure of the retina could be omitted, in addition to the fact that very high resolution images would be needed to be able to detect significant changes. Accordingly, with the help of computational tools, this diagnostic/monitoring process can be improved. This paper presents a novel strategy for the modeling of the MTA by using an estimation of distribution algorithm (EDA) based on the probability density function in order to determine the coefficients and parameters (α,β) of a Jacobi polynomial series. A model using polynomials is the novel aspect of this work since in the literature there are no models of the MTA of this type, in addition to seeking to better cover the profile of the retinal vein. According to the experimental results, the proposed method presents the advantage to achieve superior performance in terms of the mean distance to the closest point (4.34 pixels), and the Hausdorff distance (14.43 pixels) with respect to different state-of-the-art methods of the numerical modeling of the retina, using the DRIVE database of retinal fundus images with a manual delineation of the MTA performed by an specialist.
Introducción: Debido a la reciente implementación del sistema de red para la atención de pacientes con infarto agudo de miocardio con elevación del ST (IAM CEST) en México, el objetivo de este ...estudio fue comparar la mortalidad de estos pacientes por eventos cardiovasculares, la mortalidad general, tiempos de atención y complicaciones agudas en el año previo a la implementación del sistema y en el año posterior a la misma en el Instituto Mexicano del Seguro Social del estado de Guanajuato.Método: Estudio ecológico que comparó las bases de datos para evaluar la mortalidad general, por eventos cardiovasculares y complicaciones de los pacientes con IAM CEST en el año pre (2016, n=142) y post (2017, n=123) implementación del “código infarto” de pacientes en la región del Bajío, que recibieron Intervención Coronaria Percutánea.Resultados: Se identificó una disminución significativa después de inicio del “código infarto” en el total de eventos mayores (27.4% vs. 11.3%; p = 0.001) y en la presencia de insuficiencia cardiaca (11.2% vs. 0.8%; p = 0.006); pero sin diferencia específica en la muerte no cardiaca, en la presentación de angina, arritmias no fatales, o necesidad de revascularización entre los grupos.Discusión o Conclusión: La implementación del “código infarto” en la región del Bajío, México, tiene efectos benéficos en los eventos mayores cardiovasculares y presentación de insuficiencia cardiaca.
We report the natural occurrence of M. rileyi in larval A. gemmatalis and T. ni in soybean producing regions of Altamira, Tamaulipas, and Pánuco, Veracruz, Mexico, during Aug through Dec 2017. A ...total of 380 M. rileyi-infected A. gemmatalis larvae were collected from Altamira and Pánuco. In each municipality, only 1 larval T. ni was found infected with the fungus. In Oct, the greatest number of A. gemmatalis larvae infected by M. rileyi was recorded from both municipalities.
Eigen-Gradients for Traffic Sign Recognition Gonzalez-Reyna, Sheila Esmeralda; Avina-Cervantes, Juan Gabriel; Ledesma-Orozco, Sergio Eduardo ...
Mathematical problems in engineering,
01/2013, Letnik:
2013
Journal Article
Recenzirano
Odprti dostop
Traffic sign detection and recognition systems include a variety of applications like autonomous driving, road sign inventory, and driver support systems. Machine learning algorithms provide useful ...tools for traffic sign identification tasks. However, classification algorithms depend on the preprocessing stage to obtain high accuracy rates. This paper proposes a road sign characterization method based on oriented gradient maps and the Karhunen-Loeve transform in order to improve classification performance. Dimensionality reduction may be important for portable applications on resource constrained devices like FPGAs; therefore, our approach focuses on achieving a good classification accuracy by using a reduced amount of attributes compared to some state-of-the-art methods. The proposed method was tested using German Traffic Sign Recognition Benchmark, reaching a dimensionality reduction of 99.3% and a classification accuracy of 95.9% with a Multi-Layer Perceptron.
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