Titlebook: Artificial Intelligence and Data Mining in Healthcare; Malek Masmoudi,Bassem Jarboui,Patrick Siarry Book 2021 Springer Nature Switzerland

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书目名称Artificial Intelligence and Data Mining in Healthcare影响因子(影响力)




书目名称Artificial Intelligence and Data Mining in Healthcare影响因子(影响力)学科排名




书目名称Artificial Intelligence and Data Mining in Healthcare网络公开度




书目名称Artificial Intelligence and Data Mining in Healthcare网络公开度学科排名




书目名称Artificial Intelligence and Data Mining in Healthcare被引频次




书目名称Artificial Intelligence and Data Mining in Healthcare被引频次学科排名




书目名称Artificial Intelligence and Data Mining in Healthcare年度引用




书目名称Artificial Intelligence and Data Mining in Healthcare年度引用学科排名




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书目名称Artificial Intelligence and Data Mining in Healthcare读者反馈学科排名

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Lattice Images and Structure Imagesnt of hours awarded to a team of surgeons or a given specialty, the duration of shifts, and the availability of a specific operating room for a specific team. Simulation tests on a typical case using real data are performed by both methods. The results allow us to conclude as to the superiority of t

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https://doi.org/10.1007/978-3-031-67260-6aging diseases, providing better care which leads to having better outcomes including elimination of unnecessary costs and increasing patient satisfaction..In this work, we focus on one of the main clustering methods of machine learning approaches, namely mixture models. These capable techniques hav

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Optimized Medical Image Compression for Telemedicine Applications,and normalized correlation coefficient (NCC) are quantitative measures used to evaluate the performance of the proposed algorithm and well-known existing medical image compression methods. The results showed that the quality of the reconstructed images using the proposed algorithm is much better tha

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Online Variational Learning Using Finite Generalized Inverted Dirichlet Mixture Model with Feature rning of finite generalized inverted Dirichlet (GID) mixture model for clustering medical images data by simultaneously using feature selection and image segmentation. The model allows one to adjust the mixture model parameters, number of components and features weights to tackle the challenge of ov

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Entropy-Based Variational Inference for Semi-Bounded Data Clustering in Medical Applications,aging diseases, providing better care which leads to having better outcomes including elimination of unnecessary costs and increasing patient satisfaction..In this work, we focus on one of the main clustering methods of machine learning approaches, namely mixture models. These capable techniques hav