A Hands-On Introduction to Data Analytics for Biomedical Research Article Swipe
Joshua Pickard
,
Victoria E. Sturgess
,
Katherine McDonald
,
Nicholas Rossiter
,
Kelly B. Arnold
,
Yatrik M. Shah
,
Indika Rajapakse
,
Daniel Beard
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1093/function/zqaf015
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1093/function/zqaf015
Artificial intelligence (AI) applications are having increasing impacts in the biomedical sciences. Modern AI tools enable uncovering hidden patterns in large datasets, forecasting outcomes, and numerous other applications. Despite the availability and power of these tools, the rapid expansion and complexity of AI applications can be daunting, and there is a conspicuous absence of consensus on their ethical and responsible use. Misapplication of AI can result in invalid, unclear, or biased outcomes, exacerbated by the unfamiliarity of many biomedical researchers with the underlying mathematical and computational principles. To address these challenges, this review and tutorial paper aims to achieve three primary objectives: (1) highlight prevalent data science applications in biomedical research, including data visualization, dimensionality reduction, missing data imputation, and predictive model training and evaluation; (2) provide comprehensible explanations of the mathematical foundations underpinning these methodologies; and (3) guide readers on the effective use and interpretation of software tools for implementing these methods in biomedical contexts. While introductory, this guide covers core principles essential for understanding advanced applications, empowering readers to critically interpret results, assess tools, and explore the potential and limitations of machine learning in their research. Ultimately, this paper serves as a practical foundation for biomedical researchers to confidently navigate the growing intersection of AI and biomedicine.
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Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.1093/function/zqaf015
- https://academic.oup.com/function/advance-article-pdf/doi/10.1093/function/zqaf015/62892591/zqaf015.pdf
- OA Status
- gold
- References
- 1
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4409258421Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1093/function/zqaf015Digital Object Identifier
- Title
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A Hands-On Introduction to Data Analytics for Biomedical ResearchWork title
- Type
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reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-01-01Full publication date if available
- Authors
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Joshua Pickard, Victoria E. Sturgess, Katherine McDonald, Nicholas Rossiter, Kelly B. Arnold, Yatrik M. Shah, Indika Rajapakse, Daniel BeardList of authors in order
- Landing page
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https://doi.org/10.1093/function/zqaf015Publisher landing page
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https://academic.oup.com/function/advance-article-pdf/doi/10.1093/function/zqaf015/62892591/zqaf015.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://academic.oup.com/function/advance-article-pdf/doi/10.1093/function/zqaf015/62892591/zqaf015.pdfDirect OA link when available
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Data science, Computer science, Biomedicine, Big data, Underpinning, Artificial intelligence, Grand Challenges, Toolbox, Management science, Data mining, Engineering, Bioinformatics, Civil engineering, Programming language, Biology, Operating systemTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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