<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>137(10)</volume><submitter>Hair K</submitter><pubmed_abstract>Systematic reviews and meta-analysis are the cornerstones of evidence-based decision making and priority setting. However, traditional systematic reviews are time and labour intensive, limiting their feasibility to comprehensively evaluate the latest evidence in research-intensive areas. Recent developments in automation, machine learning and systematic review technologies have enabled efficiency gains. Building upon these advances, we developed Systematic Online Living Evidence Summaries (SOLES) to accelerate evidence synthesis. In this approach, we integrate automated processes to continuously gather, synthesise and summarise all existing evidence from a research domain, and report the resulting current curated content as interrogatable databases via interactive web applications. SOLES c</pubmed_abstract><journal>Clinical science (London, England : 1979)</journal><pagination>773-784</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC10220429</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Systematic online living evidence summaries: emerging tools to accelerate evidence synthesis.</pubmed_title><pmcid>PMC10220429</pmcid><pubmed_authors>Wong C</pubmed_authors><pubmed_authors>Macleod M</pubmed_authors><pubmed_authors>Wilson E</pubmed_authors><pubmed_authors>Bannach-Brown A</pubmed_authors><pubmed_authors>Hair K</pubmed_authors><pubmed_authors>Tsang A</pubmed_authors></additional><is_claimable>false</is_claimable><name>Systematic online living evidence summaries: emerging tools to accelerate evidence synthesis.</name><description>Systematic reviews and meta-analysis are the cornerstones of evidence-based decision making and priority setting. However, traditional systematic reviews are time and labour intensive, limiting their feasibility to comprehensively evaluate the latest evidence in research-intensive areas. Recent developments in automation, machine learning and systematic review technologies have enabled efficiency gains. Building upon these advances, we developed Systematic Online Living Evidence Summaries (SOLES) to accelerate evidence synthesis. In this approach, we integrate automated processes to continuously gather, synthesise and summarise all existing evidence from a research domain, and report the resulting current curated content as interrogatable databases via interactive web applications. SOLES c</description><dates><release>2023-01-01T00:00:00Z</release><publication>2023 May</publication><modification>2025-05-18T10:49:23.835Z</modification><creation>2025-02-18T23:36:35.163Z</creation></dates><accession>S-EPMC10220429</accession><cross_references><pubmed>37219941</pubmed><doi>10.1042/CS20220494</doi></cross_references></HashMap>