Medical Data Handling Using Cloud Computing And A Proposal for Countrywide Medical System

Cloud computing is mainly studied and applied in data-intensive industries. It is rarely seen in the medical industry, though it is the most representative one of data-intensive industries and closely related to people's lives. There is no medical data interaction platform of cloud computing. This paper introduces the framework of cloud computing data interaction platform for the new rural cooperative medical care system (NCSM), which will allow for NCMS data interaction on this interactive platform.

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A Low Cost Medical Data Handling System Part II

Journal of Clinical Engineering ◽

10.1097/00004669-197907000-00009 ◽

1979 ◽

Vol 4 (3) ◽

pp. 243-254

Author(s):

MORTON D. SCHWARTZ

Keyword(s):

Low Cost ◽

Medical Data ◽

Data Handling ◽

Handling System ◽

System Part

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A Blockchain-Based Smart Contract System for Healthcare Management

Electronics ◽

10.3390/electronics9010094 ◽

2020 ◽

Vol 9 (1) ◽

pp. 94 ◽

Cited By ~ 22

Author(s):

Asma Khatoon

Keyword(s):

Food Industry ◽

Healthcare Services ◽

Medical Data ◽

Healthcare Management ◽

Medical System ◽

Medical Procedures ◽

Multiple Stakeholders ◽

Chain Management ◽

Blockchain Technology ◽

Smart Contract

Blockchain is evolving to be a secure and reliable platform for secure data sharing in application areas such as the financial sector, supply chain management, food industry, energy sector, internet of things and healthcare. In this paper, we review existing literature and applications available for the healthcare system using blockchain technology. Besides, this work also proposes multiple workflows involved in the healthcare ecosystem using blockchain technology for better data management. Different medical workflows have been designed and implemented using the ethereum blockchain platform which involves complex medical procedures like surgery and clinical trials. This also includes accessing and managing a large amount of medical data. Within the implementation of the workflows of the medical smart contract system for healthcare management, the associated cost has been estimated for this system in terms of a feasibility study which has been comprehensively presented in this paper. This work would facilitate multiple stakeholders who are involved within the medical system to deliver better healthcare services and optimize cost.

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The Application of Decision Tree Algorithm in Medical Field Based on Cloud Platform

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.347-350.3397 ◽

2013 ◽

Vol 347-350 ◽

pp. 3397-3402 ◽

Cited By ~ 2

Author(s):

Zhi Yuan Liu ◽

Jian Xi Peng ◽

Yuan Kai Yang

Keyword(s):

Decision Tree ◽

Large Scale ◽

Medical Data ◽

Medical System ◽

Seizure Type ◽

Decision Tree Algorithm ◽

Cloud Platform ◽

Tree Algorithm ◽

Data Process ◽

Distributed Decision

In the medical system, medical record is summarized, analyzed and predicted a patient seizure type and incidence. With the development of information technology, a large amount of data is to be processed. Traditional analysis algorithm could not be effectively processed to obtain the best predictive results as the data increasing. Decision tree algorithm based on cloud platform is used to record, analyze and predict patients medical data in this paper. A large number of experimental results show that distributed decision tree algorithm proposed in this paper is efficient and could complete prediction work in medical system. The algorithm has good expansibility, its very suitable for large-scale and multitude medical data process.

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Data Handling of Digital Forensics Cloud Computing

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.756-759.1739 ◽

2013 ◽

Vol 756-759 ◽

pp. 1739-1743

Author(s):

Gang Zeng

Keyword(s):

Cloud Computing ◽

Digital Forensics ◽

Data Handling ◽

Digital Devices

With development of network and digital devices, traditional digital forensics tools show their drawbacks, and investigators need new forensics tools to deal with enormous digital evidences. Therefore, this paper introduces digital forensics and cloud computing, then lists the advantages of private forensics cloud computing, proposes a model of Data Handling of Digital Forensics Cloud Computing.

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Poster: Partage des données médicales du patient en utilisant le cloud computing

10.31219/osf.io/fhe6k ◽

2019 ◽

Author(s):

Thierry Oscar Dr. Edoh ◽

Emmanuel MARQUES

Keyword(s):

Cloud Computing ◽

Data Exchange ◽

Medical Data ◽

Computing Technology

Patient medical data exchange based on cloud computing technology

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Big Data Handling Approach for Unauthorized Access of Cloud Computing

10.20944/preprints202112.0068.v1 ◽

2021 ◽

Author(s):

Abdul Razaque ◽

Shaldanbayeva Nazerke ◽

Bandar Alotaibi ◽

Munif Alotaibi ◽

Akhmetov Murat ◽

...

Keyword(s):

Cloud Computing ◽

Big Data ◽

Access Control ◽

Intrusion Detection ◽

Data Access ◽

Computing System ◽

Data Handling ◽

Unauthorized Access ◽

Data Access Control ◽

Cloud Computing System

Nowadays, cloud computing is one of the important and rapidly growing paradigms that extend its capabilities and applications in various areas of life. The cloud computing system challenges many security issues, such as scalability, integrity, confidentiality, and unauthorized access, etc. An illegitimate intruder may gain access to the sensitive cloud computing system and use the data for inappropriate purposes that may lead to losses in business or system damage. This paper proposes a hybrid unauthorized data handling (HUDH) scheme for Big data in cloud computing. The HUDU aims to restrict illegitimate users from accessing the cloud and data security provision. The proposed HUDH consists of three steps: data encryption, data access, and intrusion detection. HUDH involves three algorithms; Advanced Encryption Standards (AES) for encryption, Attribute-Based Access Control (ABAC) for data access control, and Hybrid Intrusion Detection (HID) for unauthorized access detection. The proposed scheme is implemented using Python and Java language. Testing results demonstrate that the HUDH can delegate computation overhead to powerful cloud servers. User confidentiality, access privilege, and user secret key accountability can be attained with more than 97% high accuracy.

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Big Data Analysis

Advancing the Power of Learning Analytics and Big Data in Education - Advances in Educational Technologies and Instructional Design ◽

10.4018/978-1-7998-7103-3.ch010 ◽

2021 ◽

pp. 208-233

Author(s):

Arpit Kumar Sharma ◽

Arvind Dhaka ◽

Amita Nandal ◽

Kumar Swastik ◽

Sunita Kumari

Keyword(s):

Cloud Computing ◽

Big Data ◽

Data Analysis ◽

Knowledge Extraction ◽

Big Data Analysis ◽

Unstructured Data ◽

Data Sets ◽

Data Handling ◽

Software And Hardware

The meaning of the term “big data” can be inferred by its name itself (i.e., the collection of large structured or unstructured data sets). In addition to their huge quantity, these data sets are so complex that they cannot be analyzed in any way using the conventional data handling software and hardware tools. If processed judiciously, big data can prove to be a huge advantage for the industries using it. Due to its usefulness, studies are being conducted to create methods to handle the big data. Knowledge extraction from big data is very important. Other than this, there is no purpose for accumulating such volumes of data. Cloud computing is a powerful tool which provides a platform for the storage and computation of massive amounts of data.

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