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This research pioneers the use of fine-tuned Large Language Models (LLMs) to automate Systematic Literature Reviews (SLRs), presenting a significant and novel contribution in integrating AI to enhance academic research methodologies.
Challenges in updating a systematic review
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Writing integrative literature reviews: Guidelines and examples
Richard J Torraco · 2005
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Synthesising qualitative and quantitative evidence: a review of possible methods
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Qualitative meta-synthesis: a question of dialoguing with texts
Lela V. Zimmer · 2006
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Choice of data extraction tools for systematic reviews depends on resources and review complexity
Mohamed B. Elamin, David N. Flynn, D. Bassler, M. Briel, P. Alonso-Coello, P. Karanicolas, G. Guyatt, G. Málaga, T. Furukawa, R. Kunz, H. Schuuenemann, M. Murad, C. Barbui, A. Cipriani, and V. Montori · 2008
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Methodological issues and challenges in data collection and analysis of qualitative meta-synthesis
Y. Xu · 2008
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The prisma statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration
A. Liberati, D. Altman, J. Tetzlaff, C. Mulrow, P. Gøtzsche, J. Ioannidis, M. Clarke, M. Clarke, P. J. Devereaux, J. Kleijnen, and D. Moher · 2009
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A typology of reviews: an analysis of 14 review types and associated methodologies
Maria J Grant and Andrew Booth · 2009
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Expediting systematic reviews: methods and implications of rapid reviews
R. Ganann, D. Ciliska, and H. Thomas · 2010
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Searching for grey literature for systematic reviews: challenges and benefits
Quenby Mahood, D. Van Eerd, and E. Irvin · 2014
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Systematic review automation technologies
Guy Tsafnat, Paul Glasziou, Miew Keen Choong, Adam Dunn, Filippo Galgani, and Enrico Coiera · 2014
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A guide to conducting a standalone systematic literature review
Chitu Okoli · 2015
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Automating data extraction in systematic reviews: a systematic review
Siddhartha R Jonnalagadda, Pankaj Goyal, and Mark D Huffman · 2015
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Extractive text summarization system to aid data extraction from full text in systematic review development
Duy Duc An Bui, Guilherme Del Fiol, John F Hurdle, and Siddhartha Jonnalagadda · 2016
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Writing integrative literature reviews: Using the past and present to explore the future
Richard J Torraco · 2016
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Meta-synthesis of qualitative research: the challenges and opportunities
Mohammed A Mohammed, R. Moles, and T. Chen · 2016
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Grey literature: An important resource in systematic reviews
Arsenio Paez · 2017
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Guidance on conducting a systematic literature review
Yu Xiao and M. Watson · 2017
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Convergent and sequential synthesis designs: implications for conducting and reporting systematic reviews of qualitative and quantitative evidence
Q. Hong, P. Pluye, Mathieu Bujold, and M. Wassef · 2017
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Text-mining techniques and tools for systematic literature reviews: A systematic literature review
Luyi Feng, Yin Kia Chiam, and Sin Kuang Lo · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Meta-analysis and the science of research synthesis
J. Gurevitch, J. Koricheva, Shinichi Nakagawa, and G. Stewart · 2018
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Meta-analysis is not an exact science: Call for guidance on quantitative synthesis decisions
Neal R Haddaway and T. Rytwinski · 2018
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Qualitative evidence synthesis for complex interventions and guideline development: clarification of the purpose, designs and relevant methods
K. Flemming, A. Booth, R. Garside, Ö. Tunçalp, and J. Noyes · 2018
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Synthesising quantitative evidence in systematic reviews of complex health interventions
J. Higgins, J. López-López, B. Becker, S. Davies, S. Dawson, J. Grimshaw, L. McGuinness, T. Moore, E. Rehfuess, James Thomas, and D. Caldwell · 2018
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Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder · 2018
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Fever: a large-scale dataset for fact extraction and verification
James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal · 2018
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How to do a systematic review: A best practice guide for conducting and reporting narrative reviews, meta-analyses, and meta-syntheses
Andy P Siddaway, A. Wood, and L. Hedges · 2019
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Visualizing a field of research: A methodology of systematic scientometric reviews
Chaomei Chen and Min Song · 2019
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Challenges in meta-analyses with observational studies
S. Metelli and A. Chaimani · 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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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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Parameter-efficient transfer learning for nlp
Calibrated language models must hallucinate
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A culturally sensitive test to evaluate nuanced gpt hallucination
Timothy R. McIntosh, Tong Liu, Teo Susnjak, Paul Watters, Alex Ng, and Malka N. Halgamuge · 2023
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Evaluating object hallucination in large vision-language models
Yifan Li, Yifan Du, Kun Zhou, Jinpeng Wang, Wayne Xin Zhao, and Ji rong Wen · 2023
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Streamlining systematic reviews: Harnessing large language models for quality assessment and risk-of-bias evaluation
A. Nashwan and Jaber H Jaradat · 2023
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Qusai Khraisha, Sophie Put, Johanna Kappenberg, Azza Warraitch, and Kristin Hadfield · 2023
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Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly · 2019
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Re-examining systematic literature review in management research: Additional benefits and execution protocols
Ralph I. Williams, L. Clark, W. R. Clark, and Deana M. Raffo · 2020
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Innovations in framework synthesis as a systematic review method
G. Brunton, S. Oliver, and James Thomas · 2020
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Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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A review on fact extraction and verification
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How large language models will disrupt data management
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Ai-generated text may have a role in evidence-based medicine
Yifan Peng, Justin F Rousseau, Edward H Shortliffe, and Chunhua Weng · 2023
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Are chatgpt and large language models “the answer” to bringing us closer to systematic review automation?
Riaz Qureshi, Daniel Shaughnessy, Kayden AR Gill, Karen A Robinson, Tianjing Li, and Eitan Agai · 2023
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Automating systematic literature reviews with natural language processing and text mining: A systematic literature review
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Cheap, quick, and rigorous: artificial intelligence and the systematic literature review
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Rohun Gupta, Isabel Herzog, Joseph Weisberger, John Chao, Kongkrit Chaiyasate, and Edward S Lee · 2023
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Methods for using bing’s ai-powered search engine for data extraction for a systematic review
James Edward Hill, Catherine Harris, and Andrew Clegg · 2023
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Leveraging the potential of generative ai to accelerate systematic literature reviews: An example in the area of educational technology
Pablo Castillo-Segura, Carlos Alario-Hoyos, Carlos Delgado Kloos, and Carmen Fernández Panadero · 2023
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Analysis of chatgpt tool to assess the potential of its utility for academic writing in biomedical domain
Arun HS Kumar · 2023
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Harnessing the power of chatgpt for automating systematic review process: Methodology, case study, limitations, and future directions
Ahmad Alshami, Moustafa Elsayed, Eslam Ali, Abdelrahman EE Eltoukhy, and Tarek Zayed · 2023
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Truth or lies? the pitfalls and limitations of chatgpt in systematic review creation
Daniel Najafali, Justin M Camacho, Erik Reiche, Logan G Galbraith, Shane D Morrison, and Amir H Dorafshar · 2023
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Characterizing attribution and fluency tradeoffs for retrieval-augmented large language models, 2023
Renat Aksitov, Chung-Ching Chang, David Reitter, Siamak Shakeri, and Yunhsuan Sung · 2023
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How language model hallucinations can snowball, 2023
Muru Zhang, Ofir Press, William Merrill, Alisa Liu, and Noah A. Smith · 2023
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Self-rag: Learning to retrieve, generate, and critique through self-reflection
Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi · 2023
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Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer · 2023
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Neftune: Noisy embeddings improve instruction finetuning
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