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Systematic Reviews as Topic

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Performance and usability of machine learning for screening in systematic reviews: a comparative evaluation of three tools.

Systematic reviews
BACKGROUND: We explored the performance of three machine learning tools designed to facilitate title and abstract screening in systematic reviews (SRs) when used to (a) eliminate irrelevant records (automated simulation) and (b) complement the work o...

Exploring semantic deep learning for building reliable and reusable one health knowledge from PubMed systematic reviews and veterinary clinical notes.

Journal of biomedical semantics
BACKGROUND: Deep Learning opens up opportunities for routinely scanning large bodies of biomedical literature and clinical narratives to represent the meaning of biomedical and clinical terms. However, the validation and integration of this knowledge...

Toward systematic review automation: a practical guide to using machine learning tools in research synthesis.

Systematic reviews
Technologies and methods to speed up the production of systematic reviews by reducing the manual labour involved have recently emerged. Automation has been proposed or used to expedite most steps of the systematic review process, including search, sc...

Introducing RAPTOR: RevMan Parsing Tool for Reviewers.

Systematic reviews
BACKGROUND: Much effort is made to ensure Cochrane reviews are based on reliably extracted data. There is a commitment to wide access to these data-for novel processing and/or reuse-but delivering this access is problematic.

A question of trust: can we build an evidence base to gain trust in systematic review automation technologies?

Systematic reviews
BACKGROUND: Although many aspects of systematic reviews use computational tools, systematic reviewers have been reluctant to adopt machine learning tools.

Refining humane endpoints in mouse models of disease by systematic review and machine learning-based endpoint definition.

ALTEX
Ideally, humane endpoints allow for early termination of experiments by minimizing an animal's discomfort, distress and pain, while ensuring that scientific objectives are reached. Yet, lack of commonly agreed methodology and heterogeneity of cut-off...

Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error.

Systematic reviews
BACKGROUND: Here, we outline a method of applying existing machine learning (ML) approaches to aid citation screening in an on-going broad and shallow systematic review of preclinical animal studies. The aim is to achieve a high-performing algorithm ...

Extending PubMed searches to ClinicalTrials.gov through a machine learning approach for systematic reviews.

Journal of clinical epidemiology
OBJECTIVES: Despite their essential role in collecting and organizing published medical literature, indexed search engines are unable to cover all relevant knowledge. Hence, current literature recommends the inclusion of clinical trial registries in ...

Automated screening of research studies for systematic reviews using study characteristics.

Systematic reviews
BACKGROUND: Screening candidate studies for inclusion in a systematic review is time-consuming when conducted manually. Automation tools could reduce the human effort devoted to screening. Existing methods use supervised machine learning which train ...

Technology-assisted title and abstract screening for systematic reviews: a retrospective evaluation of the Abstrackr machine learning tool.

Systematic reviews
BACKGROUND: Machine learning tools can expedite systematic review (SR) processes by semi-automating citation screening. Abstrackr semi-automates citation screening by predicting relevant records. We evaluated its performance for four screening projec...