B
Babatunde K. Olorisade
Researcher at University of Bristol
Publications - 8
Citations - 204
Babatunde K. Olorisade is an academic researcher from University of Bristol. The author has contributed to research in topics: Data extraction & Systematic review. The author has an hindex of 4, co-authored 7 publications receiving 92 citations. Previous affiliations of Babatunde K. Olorisade include Cardiff Metropolitan University.
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Journal ArticleDOI
The impact of the COVID-19 pandemic on self-harm and suicidal behaviour: update of living systematic review
Ann John,Emily Eyles,Emily Eyles,Roger T. Webb,Roger T. Webb,Chukwudi Okolie,Lena Schmidt,Ella Arensman,Keith Hawton,Keith Hawton,Rory C. O'Connor,Nav Kapur,Nav Kapur,Paul Moran,Paul Moran,Siobhan O'Neill,Luke A McGuiness,Babatunde K. Olorisade,Dana Dekel,Catherine Macleod-Hall,Hung-Yuan Cheng,Julian P.T. Higgins,Julian P.T. Higgins,David Gunnell,David Gunnell +24 more
TL;DR: There is thus far no clear evidence of an increase in suicide, self-harm, suicidal behaviour, or suicidal thoughts associated with the COVID-19 pandemic, however, suicide data are challenging to collect in real time and economic effects are evolving.
Journal ArticleDOI
The impact of the COVID-19 pandemic on self-harm and suicidal behaviour: update of living systematic review [version 2; peer review: 1 approved, 2 approved with reservations]
Ann John,Emily Eyles,Roger T. Webb,Chukwudi Okolie,Lena Schmidt,Ella Arensman,Keith Hawton,Rory C. O'Connor,Nav Kapur,Paul Moran,Siobhan O'Neill,Luke A McGuinness,Babatunde K. Olorisade,Dana Dekel,Catherine Macleod-Hall,Hung-Yuan Cheng,Julian P T Higgins,David Gunnell +17 more
Journal ArticleDOI
Data extraction methods for systematic review (semi)automation: A living systematic review
Lena Schmidt,Lena Schmidt,Babatunde K. Olorisade,Babatunde K. Olorisade,Luke A McGuinness,James Thomas,Julian P T Higgins +6 more
TL;DR: A broad evidence base of publications describing data extraction for interventional reviews and a small number of publications extracting epidemiological or diagnostic accuracy data are identified.
Journal ArticleDOI
Data extraction methods for systematic review (semi)automation: A living review protocol.
TL;DR: In this article, a living review of data extraction methods and tools for data extraction is presented to support the early stages of the systematic review process, where it is currently impossible to search for relevant research with precision.
Data Extraction Methods for Systematic Review (semi)Automation: A Living Review
TL;DR: A living review of published methods and tools for data extraction to (semi)automate the systematic reviewing process and increase transparency in the reporting and assessment of machine learning technologies to the benefit of data scientists, systematic reviewers and funders of health research.