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Medical systematic reviews can be very costly and resource intensive.
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Raffel, C.; Shazeer, N.; Roberts, A.; Lee, K.; Narang, S.; Matena, M.; Zhou, Y.; Li, W.; and Liu, P. J. 2019 · 1910
Earlier work this paper cites.
A Study Design to Investigate the Effect of Intense Tai Chi in Reducing Falls among Older Adults Transitioning to Frailty
Wolf, S. L.; Sattin, R. W.; O’Grady, M.; Freret, N.; Ricci, L.; Greenspan, A. I.; Xu, T.; and Kutner, M. 2001 · 2001
Earlier work this paper cites.
Language Models are Few-Shot Learners
Brown, T. B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T.; Child, R.; Ramesh, A.; Ziegler, D. M.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; and Amodei, D. 2020 · 2005
Earlier work this paper cites.
Natural language processing with Python: analyzing text with the natural language toolkit
Bird, S.; Klein, E.; and Loper, E. 2009 · 2009
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Semi-Automated Screening of Biomedical Citations for Systematic Reviews
Wallace, B. C.; Trikalinos, T. A.; Lau, J.; Brodley, C.; and Schmid, C. H. 2010 · 2010
Earlier work this paper cites.
Scikit-learn: Machine learning in Python
Pedregosa, F.; Varoquaux, G.; Gramfort, A.; Michel, V.; Thirion, B.; Grisel, O.; Blondel, M.; Prettenhofer, P.; Weiss, R.; Dubourg, V.; et al. 2011 · 2011
Earlier work this paper cites.
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning
Aghajanyan, A.; Zettlemoyer, L.; and Gupta, S. 2020 · 2012
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Interventions for Preventing Falls in Older People Living in the Community
Gillespie, L. D.; Robertson, M. C.; Gillespie, W. J.; Sherrington, C.; Gates, S.; Clemson, L.; and Lamb, S. E. 2012 · 2012
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Deploying an Interactive Machine Learning System in an Evidence-Based Practice Center: Abstrackr
Wallace, B. C.; Small, K.; Brodley, C. E.; Lau, J.; and Trikalinos, T. A. 2012 · 2012
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How to Make Sense of a Cochrane Systematic Review
Cates, C. J.; Stovold, E.; and Welsh, E. J. 2014 · 2014
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PICO, PICOS and SPIDER: A Comparison Study of Specificity and Sensitivity in Three Search Tools for Qualitative Systematic Reviews
Methley, A. M.; Campbell, S.; Chew-Graham, C.; McNally, R.; and Cheraghi-Sohi, S. 2014 · 2014
Earlier work this paper cites.
Reducing Systematic Review Workload through Certainty-Based Screening
Miwa, M.; Thomas, J.; O’Mara-Eves, A.; and Ananiadou, S. 2014 · 2014
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Learning to Identify Relevant Studies for Systematic Reviews Using Random Forest and External Information
Khabsa, M.; Elmagarmid, A.; Ilyas, I.; Hammady, H.; and Ouzzani, M. 2016 · 2016
Earlier work this paper cites.
MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
Nguyen, T.; Rosenberg, M.; Song, X.; Gao, J.; Tiwary, S.; Majumder, R.; and Deng, L. 2016 · 2016
Earlier work this paper cites.
Use of Cost-Effectiveness Analysis to Compare the Efficiency of Study Identification Methods in Systematic Reviews
Shemilt, I.; Khan, N.; Park, S.; and Thomas, J. 2016 · 2016
Earlier work this paper cites.
Deep reinforcement learning from human preferences
Christiano, P. F.; Leike, J.; Brown, T.; Martic, M.; Legg, S.; and Amodei, D. 2017 · 2017
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Can Abstract Screening Workload Be Reduced Using Text Mining? User Experiences of the Tool Rayyan
Olofsson, H.; Brolund, A.; Hellberg, C.; Silverstein, R.; Stenström, K.; Österberg, M.; and Dagerhamn, J. 2017 · 2017
Earlier work this paper cites.
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
Shazeer, N.; Mirhoseini, A.; Maziarz, K.; Davis, A.; Le, Q. V.; Hinton, G. E.; and Dean, J. 2017 · 2017
Earlier work this paper cites.
Identifying Reports of Randomized Controlled Trials (RCTs) via a Hybrid Machine Learning and Crowdsourcing Approach
Wallace, B. C.; Noel-Storr, A.; Marshall, I. J.; Cohen, A. M.; Smalheiser, N. R.; and Thomas, J. 2017 · 2017
Cited alongside, same era.
Machine Learning for Identifying Randomized Controlled Trials: An Evaluation and Practitioner’s Guide
Marshall, I. J.; Noel-Storr, A.; Kuiper, J.; Thomas, J.; and Wallace, B. C. 2018 · 2018
Cited alongside, same era.
Prioritising References for Systematic Reviews with RobotAnalyst: A User Study
Przybyła, P.; Brockmeier, A. J.; Kontonatsios, G.; Le Pogam, M.-A.; McNaught, J.; von Elm, E.; Nolan, K.; and Ananiadou, S. 2018 · 2018
Cited alongside, same era.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2019 · 2019
Cited alongside, same era.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Lee, J.; Yoon, W.; Kim, S.; Kim, D.; Kim, S.; So, C. H.; and Kang, J. 2019 · 2019
Cited alongside, same era.
Multitask Prompted Training Enables Zero-Shot Task Generalization
Sanh, V.; Webson, A.; Raffel, C.; Bach, S. H.; Sutawika, L.; Alyafeai, Z.; Chaffin, A.; Stiegler, A.; Scao, T. L.; Raja, A.; Dey, M.; Bari, M. S.; Xu, C.; Thakker, U.; Sharma, S. S.; Szczechla, E.; Kim, T.; Chhablani, G.; Nayak, N.; Datta, D.; Chang, J.; Jiang, M. T.-J.; Wang, H.; Manica, M.; Shen, S.; Yong, Z. X.; Pandey, H.; Bawden, R.; Wang, T.; Neeraj, T.; Rozen, J.; Sharma, A.; Santilli, A.; Fevry, T.; Fries, J. A.; Teehan, R.; Bers, T.; Biderman, S.; Gao, L.; Wolf, T.; and Rush, A. M. 2022 · 2022
Later among the works it cites.
Neural Rankers for Effective Screening Prioritisation in Medical Systematic Review Literature Search
Wang, S.; Scells, H.; Koopman, B.; and Zuccon, G. 2022 · 2022
Later among the works it cites.
FINETUNED LANGUAGE MODELS ARE ZERO-SHOT LEARNERS
Wei, J.; Bosma, M.; Zhao, V. Y.; Guu, K.; Yu, A. W.; Lester, B.; Du, N.; Dai, A. M.; and Le, Q. V. 2022 · 2022
Later among the works it cites.
Goldilocks: Just-Right Tuning of BERT for Technology-Assisted Review
Yang, E.; MacAvaney, S.; Lewis, D. D.; and Frieder, O. 2022 · 2022
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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
Michelson, M.; and Reuter, K. 2019 · 2019
Cited alongside, same era.
A Step by Step Guide for Conducting a Systematic Review and Meta-Analysis with Simulation Data
Tawfik, G. M.; Dila, K. A. S.; Mohamed, M. Y. F.; Tam, D. N. H.; Kien, N. D.; Ahmed, A. M.; and Huy, N. T. 2019 · 2019
Cited alongside, same era.
A Comparison of Patient, Intervention, Comparison, Outcome (PICO) to a New, Alternative Clinical Question Framework for Search Skills, Search Results, and Self-Efficacy: A Randomized Controlled Trial
Kloda, L. A.; Boruff, J. T.; and Cavalcante, A. S. 2020 · 2020
Cited alongside, same era.
Exploring and Predicting Transferability across NLP Tasks
Vu, T.; Wang, T.; Munkhdalai, T.; Sordoni, A.; Trischler, A.; Mattarella-Micke, A.; Maji, S.; and Iyyer, M. 2020 · 2020
Cited alongside, same era.
8-bit optimizers via block-wise quantization
Dettmers, T.; Lewis, M.; Shleifer, S.; and Zettlemoyer, L. 2021 · 2021
Cited alongside, same era.
Rethink Training of BERT Rerankers in Multi-Stage Retrieval Pipeline
Gao, L.; Dai, Z.; and Callan, J. 2021 · 2021
Cited alongside, same era.
LoRA: Low-Rank Adaptation of Large Language Models
Hu, E. J.; Shen, Y.; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; Wang, L.; and Chen, W. 2021 · 2021
Cited alongside, same era.
How Cochrane Is Using Microsoft Technology to Improve the Efficiency of Systematic Review Production
2017 · 2023
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How Is ChatGPT’s Behavior Changing over Time?
Chen, L.; Zaharia, M.; and Zou, J. 2023 · 2023
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Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality
Chiang, W.-L.; Li, Z.; Lin, Z.; Sheng, Y.; Wu, Z.; Zhang, H.; Zheng, L.; Zhuang, S.; Zhuang, Y.; Gonzalez, J. E.; Stoica, I.; and Xing, E. P. 2023 · 2023
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QLoRA: Efficient Finetuning of Quantized LLMs
Dettmers, T.; Pagnoni, A.; Holtzman, A.; and Zettlemoyer, L. 2023 · 2023
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Automated Paper Screening for Clinical Reviews Using Large Language Models
Guo, E.; Gupta, M.; Deng, J.; Park, Y.-J.; Paget, M.; and Naugler, C. 2023 · 2023
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The Flan Collection: Designing Data and Methods for Effective Instruction Tuning
Longpre, S.; Hou, L.; Vu, T.; Webson, A.; Chung, H. W.; Tay, Y.; Zhou, D.; Le, Q. V.; Zoph, B.; Wei, J.; and Roberts, A. 2023 · 2023
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A Novel Application of Machine Learning and Zero-Shot Classification Methods for Automated Abstract Screening in Systematic Reviews
Moreno-Garcia, C. F.; Jayne, C.; Elyan, E.; and Aceves-Martins, M. 2023 · 2023
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OpenAI. 2023 · 2023
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Are ChatGPT and Large Language Models “the Answer” to Bringing Us Closer to Systematic Review Automation?
Qureshi, R.; Shaughnessy, D.; Gill, K. A. R.; Robinson, K. A.; Li, T.; and Agai, E. 2023 · 2023
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Assessing the Ability of ChatGPT to Screen Articles for Systematic Reviews
Syriani, E.; David, I.; and Kumar, G. 2023 · 2023
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Stanford Alpaca: An Instruction-following LLaMA model
Taori, R.; Gulrajani, I.; Zhang, T.; Dubois, Y.; Li, X.; Guestrin, C.; Liang, P.; and Hashimoto, T. B. 2023 · 2023
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Llama: Open and efficient foundation language models
Touvron, H.; Lavril, T.; Izacard, G.; Martinet, X.; Lachaux, M.-A.; Lacroix, T.; Rozière, B.; Goyal, N.; Hambro, E.; Azhar, F.; et al. 2023 · 2023
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Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search?
Wang, S.; Scells, H.; Koopman, B.; and Zuccon, G. 2023 · 2023
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