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- Auffray, C., et al.
(författare)
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COVID-19 and beyond : a call for action and audacious solidarity to all the citizens and nations, it is humanity’s fight
- 2020
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Ingår i: F1000 Research. - : F1000 Research Ltd. - 2046-1402. ; 9, s. 1130-18
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Tidskriftsartikel (refereegranskat)abstract
- Background: Severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) belongs to a subgroup of coronaviruses rampant in bats for centuries. It caused the coronavirus disease 2019 (COVID-19) pandemic. Most patients recover, but a minority of severe cases experience acute respiratory distress or an inflammatory storm devastating many organs that can lead to patient death. The spread of SARS-CoV-2 was facilitated by the increasing intensity of air travel, urban congestion and human contact during the past decades. Until therapies and vaccines are available, tests for virus exposure, confinement and distancing measures have helped curb the pandemic. Vision: The COVID-19 pandemic calls for safeguards and remediation measures through a systemic response. Self-organizing initiatives by scientists and citizens are developing an advanced collective intelligence response to the coronavirus crisis. Their integration forms Olympiads of Solidarity and Health. Their ability to optimize our response to COVID-19 could serve as a model to trigger a global metamorphosis of our societies with far-reaching consequences for attacking fundamental challenges facing humanity in the 21st century. Mission: For COVID-19 and these other challenges, there is no alternative but action. Meeting in Paris in 2003, we set out to "rethink research to understand life and improve health." We have formed an international coalition of academia and industry ecosystems taking a systems medicine approach to understanding COVID-19 by thoroughly characterizing viruses, patients and populations during the pandemic, using openly shared tools. All results will be publicly available with no initial claims for intellectual property rights. This World Alliance for Health and Wellbeing will catalyze the creation of medical and health products such as diagnostic tests, drugs and vaccines that become common goods accessible to all, while seeking further alliances with civil society to bridge with socio-ecological and technological approaches that characterise urban systems, for a collective response to future health emergencies.
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| 2. |
- Gossec, L, et al.
(författare)
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EULAR points to consider for the use of big data in rheumatic and musculoskeletal diseases
- 2020
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Ingår i: Annals of the rheumatic diseases. - : BMJ. - 1468-2060 .- 0003-4967. ; 79:1, s. 69-76
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Tidskriftsartikel (refereegranskat)abstract
- Tremendous opportunities for health research have been unlocked by the recent expansion of big data and artificial intelligence. However, this is an emergent area where recommendations for optimal use and implementation are needed. The objective of these European League Against Rheumatism (EULAR) points to consider is to guide the collection, analysis and use of big data in rheumatic and musculoskeletal disorders (RMDs).MethodsA multidisciplinary task force of 14 international experts was assembled with expertise from a range of disciplines including computer science and artificial intelligence. Based on a literature review of the current status of big data in RMDs and in other fields of medicine, points to consider were formulated. Levels of evidence and strengths of recommendations were allocated and mean levels of agreement of the task force members were calculated.ResultsThree overarching principles and 10 points to consider were formulated. The overarching principles address ethical and general principles for dealing with big data in RMDs. The points to consider cover aspects of data sources and data collection, privacy by design, data platforms, data sharing and data analyses, in particular through artificial intelligence and machine learning. Furthermore, the points to consider state that big data is a moving field in need of adequate reporting of methods and benchmarking, careful data interpretation and implementation in clinical practice.ConclusionThese EULAR points to consider discuss essential issues and provide a framework for the use of big data in RMDs.
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| 3. |
- Kedra, J, et al.
(författare)
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Current status of use of big data and artificial intelligence in RMDs: a systematic literature review informing EULAR recommendations
- 2019
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Ingår i: RMD open. - : BMJ. - 2056-5933. ; 5:2, s. e001004-
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Tidskriftsartikel (refereegranskat)abstract
- To assess the current use of big data and artificial intelligence (AI) in the field of rheumatic and musculoskeletal diseases (RMDs).MethodsA systematic literature review was performed in PubMed MEDLINE in November 2018, with key words referring to big data, AI and RMDs. All original reports published in English were analysed. A mirror literature review was also performed outside of RMDs on the same number of articles. The number of data analysed, data sources and statistical methods used (traditional statistics, AI or both) were collected. The analysis compared findings within and beyond the field of RMDs.ResultsOf 567 articles relating to RMDs, 55 met the inclusion criteria and were analysed, as well as 55 articles in other medical fields. The mean number of data points was 746 million (range 2000–5 billion) in RMDs, and 9.1 billion (range 100 000–200 billion) outside of RMDs. Data sources were varied: in RMDs, 26 (47%) were clinical, 8 (15%) biological and 16 (29%) radiological. Both traditional and AI methods were used to analyse big data (respectively, 10 (18%) and 45 (82%) in RMDs and 8 (15%) and 47 (85%) out of RMDs). Machine learning represented 97% of AI methods in RMDs and among these methods, the most represented was artificial neural network (20/44 articles in RMDs).ConclusionsBig data sources and types are varied within the field of RMDs, and methods used to analyse big data were heterogeneous. These findings will inform a European League Against Rheumatism taskforce on big data in RMDs.
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