A blockchain-based information management system for academic institutions: a case study of international students’ workflow

Chen, Weiru; Bohloul, Seyed Mahdi; Ma, Yifang; Ling, Li

doi:10.1108/idd-01-2021-0010

Cited by 6 publications

(2 citation statements)

References 30 publications

(25 reference statements)

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“…Sharing ML models can lead to unintended intellectual information disclosure if the deployment of the system is not done correctly. Using thorough planning and negotiation between institutions [55] can address this limitation. The incentive mechanism for institutional collaboration could also be explored to address this limitation in future work.…”

Section: Limitationsmentioning

confidence: 99%

Architectural Design of a Blockchain-Enabled, Federated Learning Platform for Algorithmic Fairness in Predictive Health Care: Design Science Study

Liang,

Zhao,

Chen

et al. 2023

J Med Internet Res

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Background Developing effective and generalizable predictive models is critical for disease prediction and clinical decision-making, often requiring diverse samples to mitigate population bias and address algorithmic fairness. However, a major challenge is to retrieve learning models across multiple institutions without bringing in local biases and inequity, while preserving individual patients’ privacy at each site. Objective This study aims to understand the issues of bias and fairness in the machine learning process used in the predictive health care domain. We proposed a software architecture that integrates federated learning and blockchain to improve fairness, while maintaining acceptable prediction accuracy and minimizing overhead costs. Methods We improved existing federated learning platforms by integrating blockchain through an iterative design approach. We used the design science research method, which involves 2 design cycles (federated learning for bias mitigation and decentralized architecture). The design involves a bias-mitigation process within the blockchain-empowered federated learning framework based on a novel architecture. Under this architecture, multiple medical institutions can jointly train predictive models using their privacy-protected data effectively and efficiently and ultimately achieve fairness in decision-making in the health care domain. Results We designed and implemented our solution using the Aplos smart contract, microservices, Rahasak blockchain, and Apache Cassandra–based distributed storage. By conducting 20,000 local model training iterations and 1000 federated model training iterations across 5 simulated medical centers as peers in the Rahasak blockchain network, we demonstrated how our solution with an improved fairness mechanism can enhance the accuracy of predictive diagnosis. Conclusions Our study identified the technical challenges of prediction biases faced by existing predictive models in the health care domain. To overcome these challenges, we presented an innovative design solution using federated learning and blockchain, along with the adoption of a unique distributed architecture for a fairness-aware system. We have illustrated how this design can address privacy, security, prediction accuracy, and scalability challenges, ultimately improving fairness and equity in the predictive health care domain.

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Section: Limitationsmentioning

confidence: 99%

Architectural Design of a Blockchain-Enabled, Federated Learning Platform for Algorithmic Fairness in Predictive Health Care: Design Science Study

Liang,

Zhao,

Chen

et al. 2023

J Med Internet Res

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“…This condition causes a slow exchange of information and losses due to errors in recording credit applications at one of the Sharia financial institutions in Bandung. (Chen et al, 2022;Zhang et al, 2021) This condition can be overcome by a web-based credit application information system so that recording credit applications and calculations can be more effective and efficient so that they can be well documented. Because one of the Sharia financial institutions in Bandung still uses semicomputerization, the author is interested in taking the title in writing this final assignment, "Design of A Web-Based Credit Application Information System (Study At One Of The Sharia Financial Institutions In Bandung).…”

Section: Introductionmentioning

confidence: 99%

Designing A Web-Based Credit Application Information System

Supriati,

Supriatna

2023

jeme

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In today's technological developments, the role of Internet media must be addressed. The ease of doing online activities certainly must be connected to the critical role of websites in it. One of the benefits of applying the Internet in the banking sector is simplifying work processes such as processing data for credit applications. The system being used to process data at one of the Sharia financial institutions in Bandung still needs to be better organized, so it is less effective and efficient, less accurate, or errors often occur, and also takes up much space for customer documents. Therefore, the author is interested in building a system expected to overcome the problems faced by one of the Sharia financial institutions in Bandung. This system was formulated as "Designing a Web-Based Credit Application Information System (Study at one of the Sharia financial institutions in Bandung)." The method the author uses is a qualitative descriptive method. The system development method that the author uses is the object-oriented method, namely OOSE. The author used PHP, MySQL, and XAMPP as tools to create this website. The results of this accounting information system application research can help simplify data processing at one of the Sharia financial institutions in Bandung that has been running so far.

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Blockchain Technology in Higher Education Ecosystem: Unraveling the Good, Bad, and Ugly

Tahora

Saha

Sakib

et al. 2023

2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)

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A blockchain-based information management system for academic institutions: a case study of international students’ workflow

Cited by 6 publications

References 30 publications

Architectural Design of a Blockchain-Enabled, Federated Learning Platform for Algorithmic Fairness in Predictive Health Care: Design Science Study

Architectural Design of a Blockchain-Enabled, Federated Learning Platform for Algorithmic Fairness in Predictive Health Care: Design Science Study

Designing A Web-Based Credit Application Information System

Blockchain Technology in Higher Education Ecosystem: Unraveling the Good, Bad, and Ugly

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