{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T15:49:54Z","timestamp":1785512994690,"version":"3.56.0"},"reference-count":49,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,3,10]],"date-time":"2022-03-10T00:00:00Z","timestamp":1646870400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Rheumatological and dermatological disorders contribute to a significant portion of the global burden of disease. Big Data are increasingly having a more and more relevant role, being highly ubiquitous and pervasive in contemporary society and paving the way for new, unprecedented perspectives in biomedicine, including dermatology and rheumatology. Rheumatology and dermatology can potentially benefit from Big Data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A systematic review of the literature was conducted according to the \u201cPreferred Reporting Items for Systematic Reviews and Meta-Analyses\u201d (PRISMA) guidelines, mining \u201cUno per tutti\u201d, a highly integrated and automated tool\/meta-database developed at the University of Genoa, Genoa, Italy, and consisting of 20 major scholarly electronic databases, including PubMed\/MEDLINE. Big Data- or artificial intelligence-based studies were judged based on the modified Qiao\u2019s critical appraisal tool for critical methodological quality assessment of Big Data\/machine learning-based studies. Other studies designed as cross-sectional, longitudinal, or randomized investigations, reviews\/overviews or expert opinions\/commentaries were evaluated by means of the relevant \u201cJoanna Briggs Institute\u201d (JBI)\u2019s critical appraisal tool for the critical methodological quality assessment.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Fourteen papers were included in the present systematic review of the literature. Most of the studies included concerned molecular applications of Big Data, especially in the fields of genomics and post-genomics. Other studies concerned epidemiological applications, with a practical dearth of studies assessing smart and digital applications for psoriatic arthritis patients.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Big Data can be a real paradigm shift that revolutionizes rheumatological and dermatological practice and clinical research, helping to early intercept psoriatic arthritis patients. However, there are some methodological issues that should be properly addressed (like recording and association biases) and some ethical issues that should be considered (such as privacy). Therefore, further research in the field is warranted.<\/jats:p><\/jats:sec><jats:sec><jats:title>Systematic Review Registration<\/jats:title><jats:p>Registration code 10.17605\/OSF.IO\/4KCU2.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fimmu.2022.847312","type":"journal-article","created":{"date-parts":[[2022,3,10]],"date-time":"2022-03-10T10:18:33Z","timestamp":1646907513000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":17,"title":["Harnessing Big Data, Smart and Digital Technologies and Artificial Intelligence for Preventing, Early Intercepting, Managing, and Treating Psoriatic Arthritis: Insights From a Systematic Review of the Literature"],"prefix":"10.3389","volume":"13","author":[{"given":"Nicola Luigi","family":"Bragazzi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charlie","family":"Bridgewood","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdulla","family":"Watad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giovanni","family":"Damiani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jude Dzevela","family":"Kong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dennis","family":"McGonagle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2022,3,10]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1186\/s13690-020-00458-3","article-title":"History of Global Burden of Disease Assessment at the World Health Organization","volume":"78","author":"Mathers","year":"2020","journal-title":"Arch Public Health"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(18)32281-5","article-title":"Measuring Progress From 1990 to 2017 and Projecting Attainment to 2030 of the Health-Related Sustainable Development Goals for 195 Countries and Territories: A Systematic Analysis for the Global Burden of Disease Study 2017","volume":"392","year":"2018","journal-title":"Lancet"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.3390\/ijms20061475","article-title":"Psoriasis Pathogenesis and Treatment","volume":"20","author":"Rendon","year":"2019","journal-title":"Int J Mol Sci"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2021.743180","article-title":"The Global, Regional, and National Burden of Psoriasis: Results and Insights From the Global Burden of Disease 2019 Study","volume":"8","author":"Damiani","year":"2021","journal-title":"Front Med (Lausanne)"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1007\/s40744-021-00378-w","article-title":"Predictors, Risk Factors, and Incidence Rates of Psoriatic Arthritis Development in Psoriasis Patients: A Systematic Literature Review and Meta-Analysis","volume":"8","author":"Zabotti","year":"2021","journal-title":"Rheumatol Ther"},{"key":"B6","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1186\/gm178","article-title":"Predictive, Preventive, Personalized and Participatory Medicine: Back to the Future","volume":"2","author":"Auffray","year":"2010","journal-title":"Genome Med"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1016\/j.pcad.2016.08.002","article-title":"The P4 Health Spectrum - A Predictive, Preventive, Personalized and Participatory Continuum for Promoting Healthspan","volume":"59","author":"Sagner","year":"2017","journal-title":"Prog Cardiovasc Dis"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.2147\/PPA.S38578","article-title":"From P0 to P6 Medicine, a Model of Highly Participatory, Narrative, Interactive, and \"Augmented\" Medicine: Some Considerations on Salvatore Iaconesi's Clinical Story","volume":"7","author":"Bragazzi","year":"2013","journal-title":"Patient Prefer Adherence"},{"key":"B9","doi-asserted-by":"publisher","first-page":"3","DOI":"10.31138\/mjr.30.1.3","article-title":"From Rheumatology 1.0 to Rheumatology 4.0 and Beyond: The Contributions of Big Data to the Field of Rheumatology","volume":"30","author":"Bragazzi","year":"2019","journal-title":"Mediterr J Rheumatol"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.3389\/fpubh.2018.00062","article-title":"Vaccines Meet Big Data: State-Of-the-Art and Future Prospects. 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