Deploying an interactive machine learning system in an evidence-based practice center: abstrackr

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Human-in-the-loop machine learning: a state of the art (2022, background): “On the other hand, the work of Wallace et al. (2012) is the first research publication to cite explicitly the application of IML to text processing with the development of the tool abstrackr , a system for facilitating citation screening for systematic reviews.”
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning (2020, background): “Several examples of iML systems now exist, for applications including annotation of animal behavior [26], academic citation review [63], and on-demand personalized group formation [3].”
Systematic review automation technologies (2014, methodology): “Automation approaches are to use ML to infer exclusion and inclusion rules by observing a human screener [102-106], a class of algorithms called supervised ML.”
A Review of User Interface Design for Interactive Machine Learning (2018, methodology): “Wallace et al. (2012) achieved a reduction in user workload of approximately 40% by exploiting the predictions of the trained model to mark particular research papers as irrelevant.”
Using text mining for study identification in systematic reviews: a systematic review of current approaches (2015, methodology): “The bespoke systems for systematic reviews which were used in evaluations in this review are: Abstrackr [49,50], EPPI-Reviewer [31,57], GAPScreener [51] and Revis [64].”