mantisGRID: A Grid Platform for DICOM Medical Images Management in Colombia and Latin America

Ruiz, Manuel Garcia; Chaves, Alvin Garcia; Ibáñez, Carlos Ruiz; Mazo, Jorge Mario Gutierrez; Giraldo, Juan Carlos Ramírez; Echavarria, Alejandro Pelaez; Díaz, Esther María León; Restrepo, Gustavo Pelaez; Munera, Edwin Nelson Montoya; Loaiza, Bernardo Garcia; González, Sebastián Gómez

doi:10.1007/s10278-009-9265-x

Cited by 17 publications

(2 citation statements)

References 20 publications

(7 reference statements)

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“…For the implementation of the proposed blockchain model, implementation has been done by considering the single health record of size 30.82 MP that consists of a standard size of image and text that is intraoral photography of size 1.64 MB, orthodontic cephalogram of size 1.40 MB, skin lesion photography of size 22.17 MB, dental panoramic X-ray of size 0.85MB. 33 The reason behind considering the single record is to avoid the delay in processing when different records are grouped into a block. The block size is considered 1MB for the representation of the health record query.…”

Section: Algorithm For Encryption/descriptionmentioning

confidence: 99%

GAHBT: Genetic Based Hashing Algorithm for Managing and Validating Health Data Integrity in Blockchain Technology

Hanif

Waheed

Shams

et al. 2023

BHTY

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This research work proposes a method for managing, securing, and validating the health data distribution records using a genetic-based hashing algorithm in a decentralized environment. The reason behind choosing blockchain is to secure the transaction of health data and protect the data from manipulated fraudulent movement and corruption by the contributor of the chain or any individual. The path of this technology approach provides an efficient surveillance measure such as transparency of record, fraud immunity, and protection to tempering and sustaining the order of data. In medical research, this paper provides a genetic-based hashing algorithm for data security which has lower computational complexity, low space coverage, higher security and integrity, and a high avalanche effect. The simulation will show data records' validity, immunity, and integrity. The technique modified in this secure decentralized network is a cryptographic hashing algorithm for 512 bits. In this study genetic algorithm is used to generate a key that needs to be used in the encryption and decryption of medical data. A genetic algorithm is a metaheuristic approach that is inspired by the laws of genetics and is generally used to generate high-quality solutions for complex problems. Applications of genetic algorithms encourage the significance in many medical fields such as radiology, oncology, cardiology, endocrinology, surgery, oncology, and radiotherapy in health care management.

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Section: Algorithm For Encryption/descriptionmentioning

confidence: 99%

GAHBT: Genetic Based Hashing Algorithm for Managing and Validating Health Data Integrity in Blockchain Technology

Hanif

Waheed

Shams

et al. 2023

BHTY

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“…We use a health record of the size of 25.86 MB in the experiments. This is by considering that a record consists of images and texts of standard sizes, such as intraoral photography (1.64 MB), dental panoramic X-ray (0.85 MB), orthodontic cephalogram (1.20 MB) and skin lesion photography (22.17 MB) [61]. For the query application scenario, we used the block size of 1MB that represents a health record query.…”

Section: Experimental Environmentmentioning

confidence: 99%

Blockchain Paradigm for Healthcare: Performance Evaluation

Ismail

Materwala

2020

Symmetry

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Electronic health records (EHRs) have become a popular method to store and manage patients’ data in hospitals. Sharing these records makes the current healthcare data management system more accurate and cost-efficient. Currently, EHRs are stored using the client/server architecture by which each hospital retains the stewardship of the patients’ data. The records of a patient are scattered among different hospitals using heterogeneous database servers. These limitations constitute a burden towards a personalized healthcare, when it comes to offering a cohesive view and a shared, secure and private access to patients’ health history for multiple allied professionals and the patients. The data availability, privacy and security characteristics of the blockchain have a propitious future in the healthcare presenting solutions to the complexity, confidentiality, integrity, interoperability and privacy issues of the current client/server architecture-based EHR management system. This paper analyzes and compares the performance of the blockchain and the client/server paradigms. The results reveal that notable performance can be achieved using blockchain in a patient-centric approach. In addition, the immutable and valid patients’ data in the blockchain can aid allied health professionals in better prognosis and diagnosis support through machine learning and artificial intelligence.

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