2018
Overview
Big Data Medicine refers to the application of large-scale data analytics, computational methods, and information management systems to healthcare research, drug development, and clinical practice. Research published in Big Data Research on this topic addresses the foundational infrastructure required for medical big data applications, including database architectures and computing frameworks that enable the storage and analysis of vast healthcare datasets. The journal has examined the integration of computational approaches across the drug discovery pipeline, exploring how in silico modeling, in vitro experimentation, and in vivo studies collectively advance pharmaceutical design through data-intensive methods. Additionally, published work has investigated the regulatory and commercial dimensions of big data in healthcare, analyzing legal frameworks, marketing implications, and advertising considerations that arise when organizations collect, process, and utilize large volumes of patient and medical information. This topic matters because the exponential growth of electronic health records, genomic data, medical imaging, and wearable device outputs presents both opportunities and challenges for improving patient outcomes, accelerating therapeutic development, and transforming healthcare delivery while navigating complex privacy, ethical, and compliance requirements.
Research published in this journal
3 peer-reviewed articles, ranked by relevance. Each links to its DOI.
2018
2022
How this research is being cited
The 3 articles above have been cited 4 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.
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2024 · Özgür Yayınları eBooks
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2022 · International Journal of Social Science and Human Research
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2019 · Advances in intelligent systems and computing
A sample of recent works citing this journal's research on Big Data Medicine, linking to each citing work.