Computer methods and programs in biomedicine
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Comput Methods Programs Biomed · Jul 2020
Glucose outcomes of a learning-type artificial pancreas with an unannounced meal in type 1 diabetes.
Glycemic control with unannounced meals is the major challenge for artificial pancreas. In this study, we described the performance and safety of learning-type model predictive control (L-MPC) for artificial pancreas challenged by an unannounced meal in type 1 diabetes (T1D). ⋯ The L-MPC CL insulin system achieved good glycemic control challenged by an unannounced meal.
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Comput Methods Programs Biomed · Apr 2020
Predicting entropy generation in flow of non-Newtonian flow due to a stretching sheet with chemically reactive species.
We have studied the steady Darcy Forchheimer MHD generalized non-Newtonian flow of an incompressible non-linear stretched surface in the presence chemical reactive species. Darcy Forchheimer effect and chemically reactive species are considered under entropy generation. Entropy generation analysis has been essentially applied in engineering procedure in order to improve the theoretical and mathematical evaluation problems. ⋯ The physical effects of nanomaterials, skin friction coefficient, heat transfer, mass transfer and entropy generation have been illustrated for different values of involved parameters such as the Weissenberg number, magnetic field parameter, porous medium parameter, the Darcy parameter, the Lewis number, thermophoresis diffusion, the Brownian motion parameter, chemical reaction parameter and the Prandtl number. The numerical results acquired for different physical mechanism are exposing through graphs and tables.
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Comput Methods Programs Biomed · Mar 2020
LetterCorrigendum to "Predicting entropy generation in flow of non-Newtonian flow due to a stretching sheet with chemically reactive species" [Comput. Methods Prog. Biol. 187 (2020) 105246].
This is the corrigendum to our recent published research article [1] in which the analysis of non-Newtonian fluid (Williamson model) is presented in the presence of entropy generation by a stretched surface. Total entropy rate is discussed via thermodynamics second law. ⋯ Therefore, we have rewritten the above mentioned equations in correct form in this corrigendum. Note that the updated version of manuscript does not affect the scientific and physical validity of the paper.
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Comput Methods Programs Biomed · Feb 2020
Image generation by GAN and style transfer for agar plate image segmentation.
Deep learning models and specifically Convolutional Neural Networks (CNNs) are becoming the leading approach in many computer vision tasks, including medical image analysis. Nevertheless, the CNN training usually requires large sets of supervised data, which are often difficult and expensive to obtain in the medical field. To address the lack of annotated images, image generation is a promising method, which is becoming increasingly popular in the computer vision community. In this paper, we present a new approach to the semantic segmentation of bacterial colonies in agar plate images, based on deep learning and synthetic image generation, to increase the training set size. Indeed, semantic segmentation of bacterial colony is the basis for infection recognition and bacterial counting in Petri plate analysis. ⋯ The use of a small set of real data, together with synthetic images, allows obtaining comparable results with respect to using a complete set of real images. Therefore, the proposed synthetic data generator is able to address the scarcity of biomedical data and provides a scalable and cheap alternative to human ground-truth supervision.
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Comput Methods Programs Biomed · Jan 2020
Review Historical ArticleHalf a century of computer methods and programs in biomedicine: A bibliometric analysis from 1970 to 2017.
Computer Methods and Programs in Biomedicine (CMPB) is a leading international journal that presents developments about computing methods and their application in biomedical research. The journal published its first issue in 1970. In 2020, the journal celebrates the 50th anniversary. Motivated by this event, this article presents a bibliometric analysis of the publications of the journal during this period (1970-2017). ⋯ It can be concluded that CMPB is a world-renowned publication outlet for biomedical researchers which has been growing in a number of publications since 1970. The analysis also conclude that the journal is very international with publications from all over the world although today European countries are the most productive ones.