Software Quality Injection (QI): A Quality Driven Holistic Approach for Optimising Big Healthcare Data Processing

The rapid growth of big data is driving innovation in software development, with advanced analytics offering transformative opportunities in applied computing. Big Healthcare Data (BHD), characterised by multi-structured and complex data types, requires resilient and scalable architectures to effectively address critical data quality issues. This paper proposes a holistic framework for adopting advanced cloud-computing strategies to manage and optimise the unique characteristics of BHD processing. It outlines a comprehensive approach for ensuring optimal data handling for critical healthcare workflows by enhancing the system's quality attributes. The proposed framework prioritises and dynamically adjusts software functionalities in real-time, harnessing sophisticated orchestration capabilities to manage complex, multi-dimensional healthcare datasets, streamline operations, and bolster system resilience.

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Publication Details

Journal
Studies in health technology and informatics
Published
2025-04-08
DOI
https://doi.org/10.3233/shti250065
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Software Quality Injection (QI): A Quality Driven Holistic Approach for Optimising Big Healthcare Data Processing

T. S. Haddad, Simon de Lusignan, Sarah Barman, Pushpa Kumarapeli et al.
Studies in health technology and informatics
Artificial Intelligence in Healthcare
article

Software Quality Injection (QI): A Quality Driven Holistic Approach for Optimising Big Healthcare Data Processing

T. S. Haddad, Simon de Lusignan, Sarah Barman, Pushpa Kumarapeli, Souheil Khaddaj
article en

Abstract

The rapid growth of big data is driving innovation in software development, with advanced analytics offering transformative opportunities in applied computing. Big Healthcare Data (BHD), characterised by multi-structured and complex data types, requires resilient and scalable architectures to effectively address critical data quality issues. This paper proposes a holistic framework for adopting advanced cloud-computing strategies to manage and optimise the unique characteristics of BHD processing. It outlines a comprehensive approach for ensuring optimal data handling for critical healthcare workflows by enhancing the system's quality attributes. The proposed framework prioritises and dynamically adjusts software functionalities in real-time, harnessing sophisticated orchestration capabilities to manage complex, multi-dimensional healthcare datasets, streamline operations, and bolster system resilience.

Studies in health technology and informaticsVol. 323
University of Oxford (GB), Kingston University (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 79%
Artificial Intelligence in Healthcare
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Software Quality Injection (QI): A Quality Driven Holistic Approach for Optimising Big Healthcare Data Processing — T. S. Haddad, Simon de Lusignan, et al. · Studies in health technology and informatics (2025) | TGRS Research Map | TGRS