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Titlebook: Bangabandhu and Digital Bangladesh; First International A. K. M. Muzahidul Islam,Jia Uddin,Shah Murtaza Ra Conference proceedings 2022 The

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樓主: Filament
21#
發(fā)表于 2025-3-25 05:13:01 | 只看該作者
22#
發(fā)表于 2025-3-25 10:08:26 | 只看該作者
,New Model to?Store and?Manage Private Healthcare Records Securely Using Block Chain Technologies,ive techniques in managing the health care data. With the use of new techniques, we can bring more transparency and security in the health care records management which will be much useful to the patients and to the doctors. To overcome this problem, we developed new model using block chain technology
23#
發(fā)表于 2025-3-25 13:29:31 | 只看該作者
24#
發(fā)表于 2025-3-25 17:42:30 | 只看該作者
25#
發(fā)表于 2025-3-25 23:28:38 | 只看該作者
https://doi.org/10.1007/978-3-662-25600-8from different organisms. Experimental results show that the similarity-based methods collaboratively improve prediction performance, and are even comparable to high-performing embedding-based methods in some biological graphs. We compute the importance score of similarity-based features in order to explain the leading features in a graph.
26#
發(fā)表于 2025-3-26 02:01:42 | 只看該作者
27#
發(fā)表于 2025-3-26 08:06:53 | 只看該作者
A Feasible Approach to Predict Survival Rates Post Lung Surgery Utilizing Machine Learning Techniqued model, we have used three methods for focusing on features: Decision Tree, ANOVA and Recursive Feature Elimination. Three classification algorithms are Decision Tree, K-Nearest Neighbors, and Gaussian Na?ve Bayes. By using Recursive Feature Elimination run over Decision tree classifier, our proposed model has given 89.00% accuracy on it.
28#
發(fā)表于 2025-3-26 10:17:32 | 只看該作者
29#
發(fā)表于 2025-3-26 15:38:07 | 只看該作者
,From Competition to?Collaboration: Ensembling Similarity-Based Heuristics for?Supervised Link Predifrom different organisms. Experimental results show that the similarity-based methods collaboratively improve prediction performance, and are even comparable to high-performing embedding-based methods in some biological graphs. We compute the importance score of similarity-based features in order to explain the leading features in a graph.
30#
發(fā)表于 2025-3-26 17:39:28 | 只看該作者
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