ArticleJournal of the American Medical Informatics Association : JAMIA
Cross-topic learning for work prioritization in systematic review creation and update.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 30 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Using text mining for study identification in systematic reviews: a systematic review of current approaches.Systematic reviews · 2015Pooled it
- A Prospective Evaluation of an Automated Classification System to Support Evidence-based Medicine and Systematic Review.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2010Pooled it
- Comparing supervised machine learning and large language models in title-abstract screening.Systematic reviews · 2026Article
- The landscape of artificial intelligence tools and platforms for evidence synthesis: a scoping review.Systematic reviews · 2026Article
- Large language model-based multiagent collaboration for abstract screening toward automated systematic reviews.Biology methods & protocols · 2026Article
- The hunt for the last relevant paper: blending the best of humans and AI.European journal of psychotraumatology · 2025Article
- ASReview LAB v.2: Open-source text screening with multiple agents and a crowd of experts.Patterns (New York, N.Y.) · 2025Article
- A living critical interpretive synthesis to yield a framework on the production and dissemination of living evidence syntheses for decision-making.Implementation science : IS · 2024Review
- A question-answering framework for automated abstract screening using large language models.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Machine learning to optimize literature screening in medical guideline development.Systematic reviews · 2024Article
- Automation of systematic reviews of biomedical literature: a scoping review of studies indexed in PubMed.Systematic reviews · 2024Article
- Performance of active learning models for screening prioritization in systematic reviews: a simulation study into the Average Time to Discover relevant records.Systematic reviews · 2023Article
- MMiDaS-AE: Multi-modal Missing Data aware Stacked Autoencoder for Biomedical Abstract Screening.Proceedings of the ACM Conference on Health, Inference, and Learning · 2020Article
- Improving reference prioritisation with PICO recognition.BMC medical informatics and decision making · 2019Article
- Study-based registers reduce waste in systematic reviewing: discussion and case report.Systematic reviews · 2019Article
- Trial2rev: Combining machine learning and crowd-sourcing to create a shared space for updating systematic reviews.JAMIA open · 2019Article
- Prioritising references for systematic reviews with RobotAnalyst: A user study.Research synthesis methods · 2018Article
- A Deep Learning Method to Automatically Identify Reports of Scientifically Rigorous Clinical Research from the Biomedical Literature: Comparative Analytic Study.Journal of medical Internet research · 2018Article
- Improving Endpoint Detection to Support Automated Systematic Reviews.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
- Automatically finding relevant citations for clinical guideline development.Journal of biomedical informatics · 2015Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
Abstract
objectiveMachine learning systems can be an aid to experts performing systematic reviews (SRs) by automatically ranking journal articles for work-prioritization. This work investigates whether a topic-specific automated document ranking system for SRs can be improved using a hybrid approach, combining topic-specific training data with data from other SR topics.
designA test collection was built using annotated reference files from 24 systematic drug class reviews. A support vector machine learning algorithm was evaluated with cross-validation, using seven different fractions of topic-specific training data in combination with samples from the other 23 topics. This approach was compared to both a baseline system, which used only topic-specific training data, and to a system using only the nontopic data sampled from the remaining topics. MEASUREMENTS: Mean area under the receiver-operating curve (AUC) was used as the measure of comparison.
resultsOn average, the hybrid system improved mean AUC over the baseline system by 20%, when topic-specific training data were scarce. The system performed significantly better than the baseline system at all levels of topic-specific training data. In addition, the system performed better than the nontopic system at all but the two smallest fractions of topic specific training data, and no worse than the nontopic system with these smallest amounts of topic specific training data.
conclusionsAutomated literature prioritization could be helpful in assisting experts to organize their time when performing systematic reviews. Future work will focus on extending the algorithm to use additional sources of topic-specific data, and on embedding the algorithm in an interactive system available to systematic reviewers during the literature review process.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.