WITHDRAWN: Benchmarking swarm intelligence clustering algorithms with case study of medical data

2016 ◽  
Author(s):  
Xiaoping Min ◽  
Liansheng Liu ◽  
Yuying He ◽  
Xueyuan Gong ◽  
Simon Fong ◽  
...  
Keyword(s):  
Swarm Intelligence ◽  
Clustering Algorithms ◽  
Medical Data

scholarly journals Comparative Research of Swarm Intelligence Clustering Algorithms for Analyzing Medical Data

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 137560-137569 ◽  
Author(s):  
Xueyuan Gong ◽  
Liansheng Liu ◽  
Simon Fong ◽  
Qiwen Xu ◽  
Tingxi Wen ◽  
...  
Keyword(s):  
Swarm Intelligence ◽  
Comparative Research ◽  
Clustering Algorithms ◽  
Medical Data

scholarly journals Correction to “Comparative Research of Swarm Intelligence Clustering Algorithms for Analyzing Medical Data”

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 110251-110251
Author(s):  
Xueyuan Gong ◽  
Liansheng Liu ◽  
Simon Fong ◽  
Qiwen Xu ◽  
Tingxi Wen ◽  
...  
Keyword(s):  
Swarm Intelligence ◽  
Comparative Research ◽  
Clustering Algorithms ◽  
Medical Data

scholarly journals A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 786
Author(s):  
Yenny Villuendas-Rey ◽  
Eley Barroso-Cubas ◽  
Oscar Camacho-Nieto ◽  
Cornelio Yáñez-Márquez
Keyword(s):  
Swarm Intelligence ◽  
Data Clustering ◽  
Incomplete Data ◽  
Missing Values ◽  
Clustering Algorithms ◽  
Bat Algorithm ◽  
Hybrid Features ◽  
Bee Colony ◽  
Learning Tasks ◽  
Clustering Data

Swarm intelligence has appeared as an active field for solving numerous machine-learning tasks. In this paper, we address the problem of clustering data with missing values, where the patterns are described by mixed (or hybrid) features. We introduce a generic modification to three swarm intelligence algorithms (Artificial Bee Colony, Firefly Algorithm, and Novel Bat Algorithm). We experimentally obtain the adequate values of the parameters for these three modified algorithms, with the purpose of applying them in the clustering task. We also provide an unbiased comparison among several metaheuristics based clustering algorithms, concluding that the clusters obtained by our proposals are highly representative of the “natural structure” of data.

scholarly journals GIS-BASED INFECTIOUS DISEASE DATA MANAGEMENT ON A CITY SCALE, CASE STUDY OF ST. PETERSBURG, RUSSIA

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1463-1467
Author(s):  
I. Kuznetsov ◽  
E. Panidi ◽  
A. Kolesnikov ◽  
P. Kikin ◽  
V. Korovka ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Geographical Information Systems ◽  
Medical Data ◽  
Geographical Information ◽  
Infrastructure Development ◽  
Collection System ◽  
Medical Infrastructure ◽  
Availability Assessment ◽  
The City

Abstract. Medical geography and medical cartography can be denoted as classical application domains for Geographical Information Systems (GISs). GISs can be applied to retrospective analysis (e.g., human population health analysis, medical infrastructure development and availability assessment, etc.), and to operative disaster detection and management (e.g., monitoring of epidemics development and infectious diseases spread). Nevertheless, GISs still not a daily-used instrument of medical administrations, especially on the city and municipality scales. In different regions of the world situation varies, however in general case GIS-based medical data accounting and management is the object of interest for researchers and national administrations operated on global and national scales. Our study is focused onto the investigation and design of the methodology and software prototype for GIS-based support of medical administration and planning on a city scale when accounting and controlling infectious diseases. The study area is the administrative territory of the St. Petersburg (Russia). The study is based upon the medical statistics data and data collection system of the St. Petersburg city. All the medical data used in the study are impersonalized accordingly to the Russian laws.

scholarly journals Meerkat Clan Algorithm: A New Swarm Intelligence Algorithm

2018 ◽  
Vol 10 (1) ◽  
pp. 354
Author(s):  
Ahmed T. Sadiq Al-Obaidi ◽  
Hasanen S. Abdullah ◽  
Zied O. Ahmed
Keyword(s):  
Swarm Intelligence ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Traveling Salesman ◽  
Organizational Skills ◽  
Suricata Suricatta ◽  
Kalahari Desert ◽  
Intelligence Algorithm ◽  
Swarm Intelligence Algorithm

<p>Evolutionary computation and swarm intelligence meta-heuristics are exceptional instances that environment has been a never-ending source of creativeness. The behavior of bees, bacteria, glow-worms, fireflies and other beings have stirred swarm intelligence scholars to create innovative optimization algorithms. This paper proposes the Meerkat Clan Algorithm (MCA) that is a novel swarm intelligence algorithm resulting from watchful observation of the Meerkat (Suricata suricatta) in the Kalahari Desert in southern Africa. This animal shows an exceptional intelligence, tactical organizational skills, and remarkable directional cleverness in its traversal of the desert when searching for food. A Meerkat Clan Algorithm (MCA) proposed to solve the optimization problems through reach the optimal solution by efficient way comparing with another swarm intelligence. Traveling Salesman Problem uses as a case study to measure the capacity of the proposed algorithm through comparing its results with another swarm intelligence. MCA shows its capacity to solve the Traveling Salesman’s Problem. Its dived the solutions group to sub-group depend of meerkat behavior that gives a good diversity to reach an optimal solution. Paralleled with the current algorithms for resolving TSP by swarm intelligence, it has been displayed that the size of the resolved problems could be enlarged by adopting the algorithm proposed here.</p>

Healthcare Oriented Smart House for Elderly and/or Disabled People

2010 ◽  
pp. 116-140
Author(s):  
Nicholas S. Samaras ◽  
Costas Chaikalis ◽  
Giorgios Siafakas
Keyword(s):  
Ieee 802.15.4 ◽  
Software Tool ◽  
Disabled Persons ◽  
Modern Technology ◽  
Medical Data ◽  
Automation System ◽  
Web Interface ◽  
Medical Sensors ◽  
Smart House

Smart houses represent a modern technology which can secure and facilitate our life. The objective of this chapter is to adapt medical sensors to home automated systems, which collect medical data such as blood pressure, heart rate and electrical heart activity for elderly and/or disabled persons. Firstly, the collected data is transferred to a home server and to an external manager for further analysis. Subsequently, data is stored at a database where monitoring is available only for authorized users via a simple web interface. The IEEE 802.15.4 wireless standard has been chosen as the preferred solution for communication in the smart house. Finally, two implementation scenarios of the smart house for an elderly and/or disabled person are simulated using the Custodian software tool. This case study shows that simulating the automation system of a smart house before the implementation is advantageous.

Framework Design and Case Study for Privacy-Preserving Medical Data Publishing

2013 ◽  
Vol 4 (4) ◽  
pp. 48-65 ◽  
Author(s):  
Yu Niu ◽  
Ji-Jiang Yang ◽  
Qing Wang
Keyword(s):  
Data Sharing ◽  
Personal Information ◽  
Real Life ◽  
Privacy Preserving ◽  
Medical Data ◽  
Data Publishing ◽  
Free Text ◽  
Patient Privacy ◽  
Healthcare Data

With the pervasive using of Electronic Medical Records (EMR) and telemedicine technologies, more and more digital healthcare data are accumulated from multiple sources. As healthcare data is valuable for both commercial and scientific research, the demand of sharing healthcare data has been growing rapidly. Nevertheless, health care data normally contains a large amount of personal information, and sharing them directly would bring huge threaten to the patient privacy. This paper proposes a privacy preserving framework for medical data sharing with the view of practical application. The framework focuses on three key issues of privacy protection during the data sharing, which are privacy definition/detection, privacy policy management, and privacy preserving data publishing. A case study for Chinese Electronic Medical Record (ERM) publishing with privacy preserving is implemented based on the proposed framework. Specific Chinese free text EMR segmentation, Protected Health Information (PHI) extraction, and K-anonymity PHI anonymous algorithms are proposed in each component. The real-life data from hospitals are used to evaluate the performance of the proposed framework and system.

scholarly journals A Fog Computing-Based Architecture for Medical Records Management

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Cícero A. Silva ◽  
Gibeon S. Aquino ◽  
Sávio R. M. Melo ◽  
Dannylo J. B. Egídio
Keyword(s):  
Medical Records ◽  
Fog Computing ◽  
Medical Data ◽  
Data Sources ◽  
Medical Applications ◽  
Records Management ◽  
Medical Field ◽  
Computing Paradigm ◽  
And Storage

The aging of the world’s population and the growth in the number of people with chronic diseases have increased expenses with medical care. Thus, the use of technological solutions has been widely adopted in the medical field to improve the patients’ health. In this context, approaches based on Cloud Computing have been used to store and process the information generated in these solutions. However, using Cloud can create delays that are intolerable for medical applications. Thus, the Fog Computing paradigm emerged as an alternative to overcome this problem, bringing computation and storage closer to the data sources. However, managing medical data stored in Fog is still a challenge. Moreover, characteristics of availability, performance, interoperability, and privacy need to be considered in approaches that aim to explore this problem. So, this article shows a software architecture based on Fog Computing and designed to facilitate the management of medical records. This architecture uses Blockchain concepts to provide the necessary privacy features and to allow Fog Nodes to carry out the authorization process in a distributed way. Finally, this paper describes a case study that evaluates the performance, privacy, and interoperability requirements of the proposed architecture in a home-centered healthcare scenario.

The Application of Swarm Intelligence to Collective Robots

2006 ◽  
pp. 157-185 ◽  
Author(s):  
Amanda J.C. Sharkey ◽  
Noel Sharkey
Keyword(s):  
Swarm Intelligence ◽  
Proof Of Concept ◽  
Practical Application ◽  
Predator Prey ◽  
Expected Benefits ◽  
Intelligent Approach ◽  
Intelligence Approach ◽  
Robotic Applications ◽  
Study Application

This chapter considers the application of swarm intelligence principles to collective robotics. Our aim is to identify the reasons for the growing interest in the intersection of these two areas, and to evaluate the progress that has been made to date. In the course of this chapter, we will discuss the implications of taking a swarm intelligent approach, and review recent research and applications. The area of “swarm robotics” offers considerable promise for practical application, although it is still in its infancy, and many of the tasks that have been achieved are better described as “proof-of-concept” examples, rather than full-blown applications. In the first part of the chapter, we will examine what taking a swarm intelligence approach to robotics implies, and outline its expected benefits. We shall then proceed to review recent swarm robotic applications, before concluding with a case study application of predator-prey robotics that illustrates some of the potential of the approach.

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