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Systematic literature review (SLR) is foundational to evidence-based research, enabling scholars to identify, classify, and synthesize existing studies to address specific research questions.
James lind’s treatise of the scurvy (1753)
Mary Bartholomew · 2002
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Procedures for performing systematic reviews
Barbara Kitchenham · 2004
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Guidelines for performing systematic literature reviews in software engineering, 2007
Staffs Keele et al · 2007
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A visual text mining approach for systematic reviews
Viviane Malheiros, Erika Hohn, Roberto Pinho, Manoel Mendonca, and Jose Carlos Maldonado · 2007
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Systematic literature reviews in software engineering–a systematic literature review
Barbara Kitchenham, O Pearl Brereton, David Budgen, Mark Turner, John Bailey, and Stephen Linkman · 2009
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Analysing the use of graphs to represent the results of systematic reviews in software engineering
Katia Romero Felizardo, Mehwish Riaz, Muhammad Sulayman, Emilia Mendes, Stephen G MacDonell, and José Carlos Maldonado · 2011
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Applications of text mining within systematic reviews
James Thomas, John McNaught, and Sophia Ananiadou · 2011
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A visual analysis approach to validate the selection review of primary studies in systematic reviews
Katia R Felizardo, Gabriel F Andery, Fernando V Paulovich, Rosane Minghim, and José C Maldonado · 2012
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A visual analysis approach to update systematic reviews
Katia Romero Felizardo, Elisa Yumi Nakagawa, Stephen G MacDonell, and José Carlos Maldonado · 2014
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Using text mining for study identification in systematic reviews: a systematic review of current approaches
Alison O’Mara-Eves, James Thomas, John McNaught, Makoto Miwa, and Sophia Ananiadou · 2015
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Automating data extraction in systematic reviews: a systematic review
Siddhartha R Jonnalagadda, Pawan Goyal, and Mark D Huffman · 2015
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Tool support for systematic reviews in software engineering
Christopher Marshall et al · 2016
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A critical analysis of studies that address the use of text mining for citation screening in systematic reviews
Babatunde K Olorisade, Ed de Quincey, Pearl Brereton, and Peter Andras · 2016
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Epc methods: an exploration of the use of text-mining software in systematic reviews
Robin Paynter, Lionel L Bañez, Elise Berliner, Eileen Erinoff, Jennifer Lege-Matsuura, Shannon Potter, and Stacey Uhl · 2016
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The significant cost of systematic reviews and meta-analyses: a call for greater involvement of machine learning to assess the promise of clinical trials
Matthew Michelson and Katja Reuter · 2019
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Toward systematic review automation: a practical guide to using machine learning tools in research synthesis
Iain J Marshall and Byron C Wallace · 2019
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A question of trust: can we build an evidence base to gain trust in systematic review automation technologies?
Annette M O’Connor, Guy Tsafnat, James Thomas, Paul Glasziou, Stephen B Gilbert, and Brian Hutton · 2019
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Usage of automation tools in systematic reviews
AJ Van Altena, R Spijker, and SD Olabarriaga · 2019
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A full systematic review was completed in 2 weeks using automation tools: a case study
Justin Clark, Paul Glasziou, Chris Del Mar, Alexandra Bannach-Brown, Paulina Stehlik, and Anna Mae Scott · 2020
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Text-mining techniques and tools for systematic literature reviews: A systematic literature review. in 2017 24th asia-pacific software engineering conference (apsec)(pp. 41–50)
L Feng, YK Chiam, and SK Lo · 2017
Cited alongside, same era.
(automated) literature analysis: threats and experiences
Yusra Shakeel, Jacob Krüger, Ivonne von Nostitz-Wallwitz, Christian Lausberger, Gabriel Campero Durand, Gunter Saake, and Thomas Leich · 2018
Cited alongside, same era.
Making progress with the automation of systematic reviews: principles of the international collaboration for the automation of systematic reviews (icasr)
Elaine Beller, Justin Clark, Guy Tsafnat, Clive Adams, Heinz Diehl, Hans Lund, Mourad Ouzzani, Kristina Thayer, James Thomas, Tari Turner, et al · 2018
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Machine learning techniques for the automation of literature reviews and systematic reviews in efsa
Stijn Jaspers, Ewoud De Troyer, and Marc Aerts · 2018
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Codepori: Large scale model for autonomous software development by using multi-agents
Zeeshan Rasheed, Muhammad Waseem, Mika Saari, Kari Systä, and Pekka Abrahamsson
Cited in the paper.
Zeeshan Rasheed, Muhammad Waseem, Aakash Ahmad, Kai-Kristian Kemell, Wang Xiaofeng, Anh Nguyen Duc, and Pekka Abrahamsson
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Automation of systematic literature reviews: A systematic literature review
Raymon van Dinter, Bedir Tekinerdogan, and Cagatay Catal · 2021
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Extracting training data from large language models
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, et al · 2021
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Autonomous agents in software development: A vision paper
Zeeshan Rasheed, Muhammad Waseem, Kai-Kristian Kemell, Wang Xiaofeng, Anh Nguyen Duc, Kari Systä, and Pekka Abrahamsson · 2023
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Large language models for software engineering: A systematic literature review
Xinyi Hou, Yanjie Zhao, Yue Liu, Zhou Yang, Kailong Wang, Li Li, Xiapu Luo, David Lo, John Grundy, and Haoyu Wang · 2023
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