ArticleGenetics in medicine : official journal of the American College of Medical Genetics2012
Toward modernizing the systematic review pipeline in genetics: efficient updating via data mining.
Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 4 of them syntheses that pooled it.
What it found
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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.
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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.
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Who cites it
24 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Deep Neural Network for Reducing the Screening Workload in Systematic Reviews for Clinical Guidelines: Algorithm Validation Study.Journal of medical Internet research · 2020Pooled it
- Expediting citation screening using PICo-based title-only screening for identifying studies in scoping searches and rapid reviews.Systematic reviews · 2017Pooled it
- Text mining applications in psychiatry: a systematic literature review.International journal of methods in psychiatric research · 2016Pooled it
- Using text mining for study identification in systematic reviews: a systematic review of current approaches.Systematic reviews · 2015Pooled it
- The landscape of artificial intelligence tools and platforms for evidence synthesis: a scoping review.Systematic reviews · 2026Article
- 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
- Automation of systematic reviews of biomedical literature: a scoping review of studies indexed in PubMed.Systematic reviews · 2024Article
- Article
- Applying machine classifiers to update searches: Analysis from two case studies.Research synthesis methods · 2022Article
- Machine Learning Approaches to Retrieve High-Quality, Clinically Relevant Evidence From the Biomedical Literature: Systematic Review.JMIR medical informatics · 2021Review
- Research Screener: a machine learning tool to semi-automate abstract screening for systematic reviews.Systematic reviews · 2021Article
- Refining Boolean queries to identify relevant studies for systematic review updates.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- SWIFT-Active Screener: Accelerated document screening through active learning and integrated recall estimation.Environment international · 2020Article
- The value of a second reviewer for study selection in systematic reviews.Research synthesis methods · 2019Article
- Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error.Systematic reviews · 2019Article
- Prioritising references for systematic reviews with RobotAnalyst: A user study.Research synthesis methods · 2018Article
- Meta-analysis for genome-wide association studies using case-control design: application and practice.Epidemiology and health · 2016Review
- Faster title and abstract screening? Evaluating Abstrackr, a semi-automated online screening program for systematic reviewers.Systematic reviews · 2015Article
- The use of Bayesian networks to assess the quality of evidence from research synthesis: 1.PloS one · 2015Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
purposeThe aim of this study was to demonstrate that modern data mining tools can be used as one step in reducing the labor necessary to produce and maintain systematic reviews.
methodsWe used four continuously updated, manually curated resources that summarize MEDLINE-indexed articles in entire fields using systematic review methods (PDGene, AlzGene, and SzGene for genetic determinants of Parkinson disease, Alzheimer disease, and schizophrenia, respectively; and the Tufts Cost-Effectiveness Analysis (CEA) Registry for cost-effectiveness analyses). In each data set, we trained a classification model on citations screened up until 2009. We then evaluated the ability of the model to classify citations published in 2010 as "relevant" or "irrelevant" using human screening as the gold standard.
resultsClassification models did not miss any of the 104, 65, and 179 eligible citations in PDGene, AlzGene, and SzGene, respectively, and missed only 1 of 79 in the CEA Registry (100% sensitivity for the first three and 99% for the fourth). The respective specificities were 90, 93, 90, and 73%. Had the semiautomated system been used in 2010, a human would have needed to read only 605/5,616 citations to update the PDGene registry (11%) and 555/7,298 (8%), 717/5,381 (13%), and 334/1,015 (33%) for the other three databases.
conclusionData mining methodologies can reduce the burden of updating systematic reviews, without missing more papers than humans.
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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.