AI Medical Compendium Topic

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RobotReviewer: evaluation of a system for automatically assessing bias in clinical trials.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop and evaluate RobotReviewer, a machine learning (ML) system that automatically assesses bias in clinical trials. From a (PDF-formatted) trial report, the system should determine risks of bias for the domains defined by the Cochra...

Supporting systematic reviews using LDA-based document representations.

Systematic reviews
BACKGROUND: Identifying relevant studies for inclusion in a systematic review (i.e. screening) is a complex, laborious and expensive task. Recently, a number of studies has shown that the use of machine learning and text mining methods to automatical...

Quantitative Analysis of Technological Innovation in Knee Arthroplasty: Using Patent and Publication Metrics to Identify Developments and Trends.

The Journal of arthroplasty
BACKGROUND: Surgery is in a constant continuum of innovation with refinement of technique and instrumentation. Arthroplasty surgery potentially represents an area with highly innovative process. This study highlights key area of innovation in knee ar...

Machine learning to assist risk-of-bias assessments in systematic reviews.

International journal of epidemiology
BACKGROUND: Risk-of-bias assessments are now a standard component of systematic reviews. At present, reviewers need to manually identify relevant parts of research articles for a set of methodological elements that affect the risk of bias, in order t...

Improving Endpoint Detection to Support Automated Systematic Reviews.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Authors of biomedical articles use comparison sentences to communicate the findings of a study, and to compare the results of the current study with earlier studies. The Claim Framework defines a comparison claim as a sentence that includes at least ...

PDF text classification to leverage information extraction from publication reports.

Journal of biomedical informatics
OBJECTIVES: Data extraction from original study reports is a time-consuming, error-prone process in systematic review development. Information extraction (IE) systems have the potential to assist humans in the extraction task, however majority of IE ...

Topic detection using paragraph vectors to support active learning in systematic reviews.

Journal of biomedical informatics
Systematic reviews require expert reviewers to manually screen thousands of citations in order to identify all relevant articles to the review. Active learning text classification is a supervised machine learning approach that has been shown to signi...

A corpus of potentially contradictory research claims from cardiovascular research abstracts.

Journal of biomedical semantics
BACKGROUND: Research literature in biomedicine and related fields contains a huge number of claims, such as the effectiveness of treatments. These claims are not always consistent and may even contradict each other. Being able to identify contradicto...

RevManHAL: towards automatic text generation in systematic reviews.

Systematic reviews
BACKGROUND: Systematic reviews are a key part of healthcare evaluation. They involve important painstaking but repetitive work. A major producer of systematic reviews, the Cochrane Collaboration, employs Review Manager (RevMan) programme-a software w...

Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make th...