Research Techniques Made Simple: An Introduction to Use and Analysis of Big Data in Dermatology
Open accessAbstract
Big data is a term used for any collection of datasets whose size and complexity exceeds the capabilities of traditional data processing applications. Big data repositories, including those for molecular, clinical, and epidemiology data, offer unprecedented research opportunities to help guide scientific advancement. Advantages of big data can include ease and low cost of collection, ability to approach prospectively and retrospectively, utility for hypothesis generation in addition to hypothesis testing, and the promise of precision medicine. Limitations include cost and difficulty of storing and processing data; need for advanced techniques for formatting and analysis; and concerns about accuracy, reliability, and security. We discuss sources of big data and tools for its analysis to help inform the treatment and management of dermatologic diseases.
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The source of big data and tools for its analysis can be used to help and diagnose the treatment and management of dermatologic diseases.
“It is explained that the source of big data and tools for its analysis can be used to help and diagnose the treatment and management of dermatologic diseases [53].”
From Influential Usage of Big Data and Artificial Intelligence in Healthcare (2021) · cites this paper as [53]
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Influential Usage of Big Data and Artificial Intelligence in Healthcare
Yang, Y. C., Islam, S. U., Noor, A., Khan, S., Afsar, W., & Nazir, S. (2021) · Computational and Mathematical Methods in Medicine · doi:10.1155/2021/5812499 · Cited by 68 · see citing works
“It is explained that the source of big data and tools for its analysis can be used to help and diagnose the treatment and management of dermatologic diseases [53].”
BackgroundRetracted
- Authors
- Wehner, M. R., Levandoski, K. A., Kulldorff, M., & Asgari, M. M.
- Affiliations
- University of Pennsylvania (US)
- Harvard University (US)
- Brigham and Women's Hospital (US)
- Corresponding author
- Asgari, Maryam M.
- Venue
- Journal of Investigative Dermatology
- Publisher
- Elsevier BV
- Published
- 2017-08
- Volume
- 137
- Issue
- 8
- Pages
- e153-e158
- ISSN
- 0022-202X (ISSN-L)
- PMC
- PMC5600502
- OpenAlex
- W2736750926
- Cited by
- 22
- References
- 12
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 6 · 2023: 2 · 2022: 1 · 2021: 4 · 2020: 2 · 2019: 1 · 2018: 2
- FWCI
- 2.20
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Investigative Dermatology (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Eli Lilly and Company
- Pfizer
- Valeant Pharmaceuticals International
- National Institutes of Health
- National Cancer Institute (R01CA166672)
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (K24AR069760, T32AR007465)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- big data, dermatology research, precision medicine, data analysis software, data storage and processing, data security, hypothesis generation, skin diseases
- MeSH terms
- Dermatology, Humans, Databases, Factual, Biomedical Research, Precision Medicine
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