找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

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

[复制链接]
楼主: Filament
发表于 2025-3-25 05:13:01 | 显示全部楼层
发表于 2025-3-25 10:08:26 | 显示全部楼层
,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
发表于 2025-3-25 13:29:31 | 显示全部楼层
发表于 2025-3-25 17:42:30 | 显示全部楼层
发表于 2025-3-25 23:28:38 | 显示全部楼层
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.
发表于 2025-3-26 02:01:42 | 显示全部楼层
发表于 2025-3-26 08:06:53 | 显示全部楼层
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 Naïve Bayes. By using Recursive Feature Elimination run over Decision tree classifier, our proposed model has given 89.00% accuracy on it.
发表于 2025-3-26 10:17:32 | 显示全部楼层
发表于 2025-3-26 15:38:07 | 显示全部楼层
,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.
发表于 2025-3-26 17:39:28 | 显示全部楼层
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-6-2 10:34
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表