4th International Conference on Medical Imaging with Deep Learning Jul 07, 2021 - Jul 09, 2021 — Virtual Meeting (online)
Medical Image Understanding and Analysis Conference 2021 Jul 12, 2021 - Jul 14, 2021 — Virtual Meeting (online)
Medical Imaging Convention [rescheduled] Sep 15, 2021 - Sep 16, 2021 — National Exhibition Centre, Birmingham, England
2021 SINAPSE ASM Sep 16, 2021 - Sep 17, 2021 — Technology & Innovation Centre, University of Strathclyde, 99 George Street, Glasgow
Total Body PET 2021 conference [rescheduled] Sep 22, 2021 - Sep 24, 2021 — Virtual Meeting (online)

eLearning

SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.


Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

Identifying observational studies of surgical interventions in MEDLINE and EMBASE

Author(s): Cynthia Fraser, Alison Murray, Jennifer Burr

Abstract:
BACKGROUND: Health technology assessments of surgical interventions frequently require the inclusion of non-randomised evidence. Literature search strategies employed to identify this evidence often exclude a methodological component because of uncertainty surrounding the use of appropriate search terms. This can result in the retrieval of a large number of irrelevant records. Methodological filters would help to minimise this, making literature searching more efficient. METHODS: An objective approach was employed to develop MEDLINE and EMBASE filters, using a reference standard derived from screening the results of an electronic literature search that contained only subject-related terms. Candidate terms for MEDLINE (N = 37) and EMBASE (N = 35) were derived from examination of the records of the reference standard. The filters were validated on two sets of studies that had been included in previous health technology assessments. RESULTS: The final filters were highly sensitive (MEDLINE 99.5%, EMBASE 100%, MEDLINE/EMBASE combined 100%) with precision ranging between 16.7%-21.1%, specificity 35.3%-43.5%, and a reduction in retrievals of over 30%. Against the validation standards, the individual filters retrieved 85.2%-100% of records. In combination, however, the MEDLINE and EMBASE filters retrieved 100% against both validation standards with a reduction in retrieved records of 28.4% and 30.1% CONCLUSION: The MEDLINE and EMBASE filters were highly sensitive and substantially reduced the number of records retrieved, indicating that they are useful tools for efficient literature searching.

Full version: Available here

Click the link to go to an external website with the full version of the paper


ISBN: 1471-2288
Publication Year: 2006
Periodical: BMC Med Res Methodol
Periodical Number:
Volume: 6
Pages: 41
Author Address: