Cargando…
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
BACKGROUND: 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 perspe...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8960164/ https://www.ncbi.nlm.nih.gov/pubmed/35359924 http://dx.doi.org/10.3389/fimmu.2022.847312 |
_version_ | 1784677329636687872 |
---|---|
author | Bragazzi, Nicola Luigi Bridgewood, Charlie Watad, Abdulla Damiani, Giovanni Kong, Jude Dzevela McGonagle, Dennis |
author_facet | Bragazzi, Nicola Luigi Bridgewood, Charlie Watad, Abdulla Damiani, Giovanni Kong, Jude Dzevela McGonagle, Dennis |
author_sort | Bragazzi, Nicola Luigi |
collection | PubMed |
description | BACKGROUND: 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. METHODS: A systematic review of the literature was conducted according to the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) guidelines, mining “Uno per tutti”, 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’s 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 “Joanna Briggs Institute” (JBI)’s critical appraisal tool for the critical methodological quality assessment. RESULTS: 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. CONCLUSIONS: 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. SYSTEMATIC REVIEW REGISTRATION: Registration code 10.17605/OSF.IO/4KCU2. |
format | Online Article Text |
id | pubmed-8960164 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89601642022-03-30 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 Bragazzi, Nicola Luigi Bridgewood, Charlie Watad, Abdulla Damiani, Giovanni Kong, Jude Dzevela McGonagle, Dennis Front Immunol Immunology BACKGROUND: 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. METHODS: A systematic review of the literature was conducted according to the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) guidelines, mining “Uno per tutti”, 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’s 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 “Joanna Briggs Institute” (JBI)’s critical appraisal tool for the critical methodological quality assessment. RESULTS: 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. CONCLUSIONS: 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. SYSTEMATIC REVIEW REGISTRATION: Registration code 10.17605/OSF.IO/4KCU2. Frontiers Media S.A. 2022-03-10 /pmc/articles/PMC8960164/ /pubmed/35359924 http://dx.doi.org/10.3389/fimmu.2022.847312 Text en Copyright © 2022 Bragazzi, Bridgewood, Watad, Damiani, Kong and McGonagle https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Bragazzi, Nicola Luigi Bridgewood, Charlie Watad, Abdulla Damiani, Giovanni Kong, Jude Dzevela McGonagle, Dennis 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 |
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 |
title_full | 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 |
title_fullStr | 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 |
title_full_unstemmed | 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 |
title_short | 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 |
title_sort | 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 |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8960164/ https://www.ncbi.nlm.nih.gov/pubmed/35359924 http://dx.doi.org/10.3389/fimmu.2022.847312 |
work_keys_str_mv | AT bragazzinicolaluigi harnessingbigdatasmartanddigitaltechnologiesandartificialintelligenceforpreventingearlyinterceptingmanagingandtreatingpsoriaticarthritisinsightsfromasystematicreviewoftheliterature AT bridgewoodcharlie harnessingbigdatasmartanddigitaltechnologiesandartificialintelligenceforpreventingearlyinterceptingmanagingandtreatingpsoriaticarthritisinsightsfromasystematicreviewoftheliterature AT watadabdulla harnessingbigdatasmartanddigitaltechnologiesandartificialintelligenceforpreventingearlyinterceptingmanagingandtreatingpsoriaticarthritisinsightsfromasystematicreviewoftheliterature AT damianigiovanni harnessingbigdatasmartanddigitaltechnologiesandartificialintelligenceforpreventingearlyinterceptingmanagingandtreatingpsoriaticarthritisinsightsfromasystematicreviewoftheliterature AT kongjudedzevela harnessingbigdatasmartanddigitaltechnologiesandartificialintelligenceforpreventingearlyinterceptingmanagingandtreatingpsoriaticarthritisinsightsfromasystematicreviewoftheliterature AT mcgonagledennis harnessingbigdatasmartanddigitaltechnologiesandartificialintelligenceforpreventingearlyinterceptingmanagingandtreatingpsoriaticarthritisinsightsfromasystematicreviewoftheliterature |