Extreme events in biomedical data
European Physical Journal: Special Topics, ISSN: 1951-6401
2024
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
In this paper, we provided a brief review of the study of extreme events in biomedical data. The main topics of interest were states in the living system that lead to the occurrence of extreme events, types of biomedical signals containing extreme events, extreme value theory approaches used to detect/predict extreme dynamics, the results obtained and their possible application in medical diagnostics/treatment. The main purpose of the review is to draw attention to this relevant area of research.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85210494511&origin=inward; http://dx.doi.org/10.1140/epjs/s11734-024-01415-9; https://link.springer.com/10.1140/epjs/s11734-024-01415-9; https://dx.doi.org/10.1140/epjs/s11734-024-01415-9; https://link.springer.com/article/10.1140/epjs/s11734-024-01415-9
Springer Science and Business Media LLC
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