AI Medical Compendium Journal:
Systematic reviews

Showing 31 to 40 of 49 articles

Early detection of sepsis using artificial intelligence: a scoping review protocol.

Systematic reviews
BACKGROUND: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. To decrease the high case fatality rates and morbidity for sepsis and septic shock, there is a need to increase the accuracy of early dete...

Aligning text mining and machine learning algorithms with best practices for study selection in systematic literature reviews.

Systematic reviews
BACKGROUND: Despite existing research on text mining and machine learning for title and abstract screening, the role of machine learning within systematic literature reviews (SLRs) for health technology assessment (HTA) remains unclear given lack of ...

Statistical stopping criteria for automated screening in systematic reviews.

Systematic reviews
Active learning for systematic review screening promises to reduce the human effort required to identify relevant documents for a systematic review. Machines and humans work together, with humans providing training data, and the machine optimising th...

Decoding semi-automated title-abstract screening: findings from a convenience sample of reviews.

Systematic reviews
BACKGROUND: We evaluated the benefits and risks of using the Abstrackr machine learning (ML) tool to semi-automate title-abstract screening and explored whether Abstrackr's predictions varied by review or study-level characteristics.

Machine learning for screening prioritization in systematic reviews: comparative performance of Abstrackr and EPPI-Reviewer.

Systematic reviews
BACKGROUND: Improving the speed of systematic review (SR) development is key to supporting evidence-based medicine. Machine learning tools which semi-automate citation screening might improve efficiency. Few studies have assessed use of screening pri...

The applications of machine learning in plastic and reconstructive surgery: protocol of a systematic review.

Systematic reviews
BACKGROUND: Machine learning, a subset of artificial intelligence, is a set of models and methods that can automatically detect patterns in vast amounts of data, extract information and use it to perform various kinds of decision-making under uncerta...

Assessing the accuracy of machine-assisted abstract screening with DistillerAI: a user study.

Systematic reviews
BACKGROUND: Web applications that employ natural language processing technologies to support systematic reviewers during abstract screening have become more common. The goal of our project was to conduct a case study to explore a screening approach t...

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...

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.