Screening articles for systematic reviews with ChatGPT

Scikit-learn: Machine Learning in Python

Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Müller, A., Nothman, J., Louppe, G., et al. (2012) · arXiv · doi:10.48550/arxiv.1201.0490 · Cited by 71,016 · see citing works

Distributed Representations of Words and Phrases and their Compositionality

Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1310.4546 · Cited by 24,533 · see citing works

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reimers, N., & Gurevych, I. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · doi:10.18653/v1/d19-1410 · Cited by 12,778 · see citing works

Advances in Neural Information Processing Systems 25

Zhang, Y., Sutton, C. A., Storkey, A., & Zoubin Ghahramani, A. (2012) · Cited by 12,653 · see citing works

Distributed Representations of Sentences and DocumentsPreprint

Le, Q. V., & Mikolov, T. (2014) · International Conference on Machine Learning · doi:10.48550/arxiv.1405.4053 · Cited by 10,307 · see citing works

Text categorization with Support Vector Machines: Learning with many relevant features

Joachims, T. (1998) · Lecture notes in computer science · doi:10.1007/bfb0026683 · Cited by 8,134 · see citing works

Untitled work

(2012) · Cited by 8,009 · see citing works

Untitled work

(2009) · Minds at UW (University of Wisconsin) · Cited by 4,791 · see citing works

Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing

Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G. (2023) · ACM Computing Surveys · doi:10.1145/3560815 · Cited by 4,361 · see citing works

Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing

Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G. (2021) · arXiv · doi:10.48550/arxiv.2107.13586 · Cited by 4,352 · see citing works

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., Chi, E., Le, Q., & Zhou, D. (2022) · arXiv · doi:10.48550/arxiv.2201.11903 · Cited by 4,263 · see citing works

GPT-3: Its Nature, Scope, Limits, and Consequences

Floridi, L., & Chiriatti, M. (2020) · Minds and Machines · doi:10.1007/s11023-020-09548-1 · Cited by 2,519 · see citing works

Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation

Sokolova, M., Japkowicz, N., & Szpakowicz, S. (2006) · Lecture Notes in Computer Science · doi:10.1007/11941439_114 · Cited by 1,974 · see citing works

Logistic Regression

LaValley, M. P. (2008) · Circulation · doi:10.1161/circulationaha.106.682658 · Cited by 1,163 · see citing works

An open source machine learning framework for efficient and transparent systematic reviews

van de Schoot, R., de Bruin, J., Schram, R., Zahedi, P., de Boer, J., Weijdema, F., Kramer, B., Huijts, M., Hoogerwerf, M., Ferdinands, G., et al. (2021) · Nature Machine Intelligence · doi:10.1038/s42256-020-00287-7 · Cited by 1,157 · see citing works

PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews

Page, M. J., Moher, D., Bossuyt, P., Boutron, I., Hoffmann, T., mulrow, C., Shamseer, L., Tetzlaff, J., Akl, E., Brennan, S. E., et al. (2020) · doi:10.31222/osf.io/gwdhk · Cited by 916 · see citing works

A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT

White, J., Fu, Q., Hays, S., Sandborn, M., Olea, C., Gilbert, H., Elnashar, A., Spencer-Smith, J., & Schmidt, D. C. (2023) · arXiv · doi:10.48550/arxiv.2302.11382 · Cited by 838 · see citing works

Expediting systematic reviews: methods and implications of rapid reviews

Ganann, R., Ciliska, D., & Thomas, H. (2010) · Implementation Science · doi:10.1186/1748-5908-5-56 · Cited by 752 · see citing works

Analysis of the time and workers needed to conduct systematic reviews of medical interventions using data from the PROSPERO registry

Borah, R., Brown, A. W., Capers, P. L., & Kaiser, K. A. (2017) · BMJ Open · doi:10.1136/bmjopen-2016-012545 · Cited by 737 · see citing works

A comprehensive survey on pretrained foundation models: a history from BERT to ChatGPT

Zhou, C., Li, Q., Li, C., Yu, J., Liu, Y., Wang, G., Zhang, K., Ji, C., Yan, Q., He, L., et al. (2024) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-024-02443-6 · Cited by 704 · see citing works

Role of Chat GPT in public health

Biswas, S. S. (2023) · Annals of Biomedical Engineering · doi:10.1007/s10439-023-03172-7 · Cited by 673 · see citing works

The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification

Chicco, D., & Jurman, G. (2023) · BioData Mining · doi:10.1186/s13040-023-00322-4 · Cited by 667 · see citing works

Instruction Tuning for Large Language Models: A Survey

Zhang, S., Dong, L., Li, X., Zhang, S., Sun, X., Wang, S., Li, J., Hu, R., Zhang, T., Wang, G., et al. (2025) · ACM Computing Surveys · doi:10.1145/3777411 · Cited by 640 · see citing works

Toward systematic review automation: a practical guide to using machine learning tools in research synthesis

Marshall, I. J., & Wallace, B. C. (2019) · Systematic Reviews · doi:10.1186/s13643-019-1074-9 · Cited by 638 · see citing works

The Benefits and Challenges of Using Systematic Reviews in International Development Research

Mallett, R., Hagen-Zanker, J., Slater, R., & Duvendack, M. (2012) · Journal of Development Effectiveness · doi:10.1080/19439342.2012.711342 · Cited by 565 · see citing works

Systematic review automation technologies

Tsafnat, G., Glasziou, P., Choong, M. K., Dunn, A., Galgani, F., & Coiera, E. (2014) · Systematic Reviews · doi:10.1186/2046-4053-3-74 · Cited by 472 · see citing works

Evaluation Measures for Models Assessment over Imbalanced Data Sets

Bekkar, M., Djemaa, H. K., & Alitouche, T. A. (2013) · Journals & Books Hosting (International Knowledge Sharing Platform) · Cited by 436 · see citing works

Automation of systematic literature reviews: A systematic literature review

van Dinter, R., Tekinerdogan, B., & Catal, C. (2021) · Information and Software Technology · doi:10.1016/j.infsof.2021.106589 · Cited by 432 · see citing works

Reducing Workload in Systematic Review Preparation Using Automated Citation Classification

Cohen, A. M., Hersh, W. R., Peterson, K., & Yen, P.-Y. (2006) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m1929 · Cited by 411 · see citing works

Potential Use of Chat GPT in Global Warming

Biswas, S. S. (2023) · Annals of Biomedical Engineering · doi:10.1007/s10439-023-03171-8 · Cited by 291 · see citing works

Automating data extraction in systematic reviews: a systematic review

Jonnalagadda, S. R., Goyal, P., & Huffman, M. D. (2015) · Systematic Reviews · doi:10.1186/s13643-015-0066-7 · Cited by 287 · see citing works

Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search?

Wang, S., Scells, H., Koopman, B., & Zuccon, G. (2023) · Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/3539618.3591703 · Cited by 275 · see citing works

Can large language models replace humans in systematic reviews? Evaluating <scp>GPT</scp> ‐4's efficacy in screening and extracting data from peer‐reviewed and grey literature in multiple languages

Khraisha, Q., Put, S., Kappenberg, J., Warraitch, A., & Hadfield, K. (2024) · Research Synthesis Methods · doi:10.1002/jrsm.1715 · Cited by 269 · see citing works

Can large language models replace humans in the systematic review process? Evaluating GPT-4's efficacy in screening and extracting data from peer-reviewed and grey literature in multiple languages

Khraisha, Q., Put, S., Kappenberg, J., Warraitch, A., & Hadfield, K. (2023) · arXiv · doi:10.48550/arxiv.2310.17526 · Cited by 268 · see citing works

Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems

Kitamura, Y., Kitamura, Y., Quigley, A., Isbister, K., Igarashi, T., Japan, C. '. C. C. O. H. F. I. C. S. 2. Y., Association for Computing Machinery-Digital Library, ACM Special Interest Group on Computer-Human Interaction, & SIGs, A. (2021) · doi:10.1145/3411763 · Cited by 245 · see citing works

Distribution-balanced stratified cross-validation for accuracy estimation

Zeng, X., & Martinez, T. R. (2000) · Journal of Experimental & Theoretical Artificial Intelligence · doi:10.1080/095281300146272 · Cited by 242 · see citing works

Instruction Tuning for Large Language Models: A Survey

Zhang, S., Dong, L., Li, X., Zhang, S., Sun, X., Wang, S., Li, J., Hu, R., Zhang, T., Wu, F., et al. (2023) · arXiv · doi:10.48550/arxiv.2308.10792 · Cited by 241 · see citing works

Reducing systematic review workload through certainty-based screening

Miwa, M., Thomas, J., O’Mara-Eves, A., & Ananiadou, S. (2014) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2014.06.005 · Cited by 190 · see citing works

PromptMaker: Prompt-based Prototyping with Large Language Models

Jiang, E., Olson, K., Toh, E., Molina, A., Donsbach, A., Terry, M., & Cai, C. J. (2022) · CHI Conference on Human Factors in Computing Systems Extended Abstracts · doi:10.1145/3491101.3503564 · Cited by 157 · see citing works

ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing

Arawjo, I., Swoopes, C., Vaithilingam, P., WATTENBERG, M. P., & Glassman, E. L. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642016 · Cited by 146 · see citing works

ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing

Arawjo, I., Swoopes, C., Vaithilingam, P., Wattenberg, M., & Glassman, E. (2023) · arXiv · doi:10.48550/arxiv.2309.09128 · Cited by 146

Bayesian Multinomial Naïve Bayes Classifier to Text Classification

Xu, S., Li, Y., & Wang, Z. (2017) · Lecture notes in electrical engineering · doi:10.1007/978-981-10-5041-1_57 · Cited by 126 · see citing works

AI 2006: Advances in Artificial Intelligence

(2006) · Lecture notes in computer science · doi:10.1007/11941439 · Cited by 119 · see citing works

A new algorithm for reducing the workload of experts in performing systematic reviews

Matwin, S., Kouznetsov, A., Inkpen, D., Frunza, O., & O'Blenis, P. (2010) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.2010.004325 · Cited by 100 · see citing works

Learning to identify relevant studies for systematic reviews using random forest and external information

Khabsa, M., Elmagarmid, A., Ilyas, I., Hammady, H., & Ouzzani, M. (2016) · Machine Learning · doi:10.1007/s10994-015-5535-7 · Cited by 98 · see citing works

Empirical Standards for Software Engineering ResearchPreprint

Ralph, P., bin Ali, N., Baltes, S., Bianculli, D., Díaz, J., Dittrich, Y., Ernst, N., Felderer, M., FELDT, R. H., Filieri, A., et al. (2020) · arXiv (Cornell University) · doi:10.4230/lipics.esem.2026.10 · Cited by 96 · see citing works

A Semantics Aware Random Forest for Text Classification

Islam, M. Z., Liu, J., Li, J., Liu, L., & Kang, W. (2019) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3357384.3357891 · Cited by 73 · see citing works

Integrating large language models in systematic reviews: a framework and case study using ROBINS-I for risk of bias assessment

Hasan, B., Saadi, S. M., Rajjoub, N. S., Hegazi, M., Al-Kordi, M., Fleti, F., Farah, M. H., Riaz, I. B., Banerjee, I., Wang, Z., et al. (2024) · BMJ Evidence-Based Medicine · doi:10.1136/bmjebm-2023-112597 · Cited by 72 · see citing works

Information and Knowledge Management

(2019) · doi:10.7176/ikm · Cited by 67 · see citing works

Active learning for screening prioritization in systematic reviews - A simulation study

Ferdinands, G., Schram, R., de Bruin, J., Bagheri, A., Oberski, D. L., Tummers, L., & van de Schoot, R. (2020) · doi:10.31219/osf.io/w6qbg · Cited by 51 · see citing works

Using ontology-based semantic similarity to facilitate the article screening process for systematic reviews

Ji, X., Ritter, A., & Yen, P. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.03.007 · Cited by 48 · see citing works

A Systematic Mapping Study driven by the margin of error

Kosar, T., Bohra, S., & Mernik, M. (2018) · Journal of Systems and Software · doi:10.1016/j.jss.2018.06.078 · Cited by 47 · see citing works

Paving the way for mature secondary research: the seven types of literature review

Ralph, P., & Baltes, S. (2022) · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) · doi:10.1145/3540250.3560877 · Cited by 47 · see citing works

Computer Science Papers in Web of Science: A Bibliometric Analysis

Fiala, D., & Tutoky, G. (2017) · Publications · doi:10.3390/publications5040023 · Cited by 46 · see citing works

Multi-paradigm modeling for cyber–physical systems: A systematic mapping review

Barišić, A., Ruchkin, I., Savić, D., Mohamed, M. A., Al-Ali, R., Li, L. W., Mkaouar, H., Eslampanah, R., Challenger, M., Blouin, D., et al. (2021) · Journal of Systems and Software · doi:10.1016/j.jss.2021.111081 · Cited by 42 · see citing works

Automating Systematic Literature Review

Felizardo, K. R., & Carver, J. C. (2020) · Springer eBooks · doi:10.1007/978-3-030-32489-6_12 · Cited by 41 · see citing works

Collaborative Model-Driven Software Engineering: A Systematic Update

Dávid, I., Aslam, K., Faridmoayer, S., Malavolta, I., Syriani, E., & Lago, P. (2021) · ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS) · doi:10.1109/models50736.2021.00035 · Cited by 33 · see citing works

On the Reliability of the Area Under the ROC Curve in Empirical Software Engineering

Lavazza, L., Morasca, S., & Rotoloni, G. (2023) · International Conference on Evaluation and Assessment in Software Engineering (EASE) · doi:10.1145/3593434.3593456 · Cited by 32 · see citing works

Model Driven Engineering Languages and Systems

Whittle, J., Kühne, T., & Clark, T. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-24485-8 · Cited by 28 · see citing works

Advanced Multimedia and Ubiquitous Engineering

Park, J., Chen, S., & Choo, K.-K. R. (2017) · Lecture notes in electrical engineering · doi:10.1007/978-981-10-5041-1 · Cited by 28 · see citing works

Towards Better Chain-of-Thought Prompting Strategies: A SurveyPreprint

Yu, Z., He, L., Wu, Z., Dai, X., & Chen, J. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2310.04959 · Cited by 28 · see citing works

Vision for SLR tooling infrastructure: Prioritizing value-added requirements

Al-Zubidy, A., Carver, J. C., Hale, D. P., & Hassler, E. E. (2017) · Information and Software Technology · doi:10.1016/j.infsof.2017.06.007 · Cited by 27 · see citing works

Assessing the Ability of ChatGPT to Screen Articles for Systematic Reviews

Syriani, E., David, I., & Kumar, G. (2023) · arXiv · doi:10.48550/arxiv.2307.06464 · Cited by 27 · see citing works

Reducing efforts of software engineering systematic literature reviews updates using text classification

Watanabe, W. M., Felizardo, K. R., Cândido, A., de Souza, É. F., Neto, J. E. D. C., & Vijaykumar, N. L. (2020) · Information and Software Technology · doi:10.1016/j.infsof.2020.106395 · Cited by 25 · see citing works

An analysis of work saved over sampling in the evaluation of automated citation screening in systematic literature reviews

Kusa, W., Lipani, A., Knoth, P., & Hanbury, A. (2023) · Intelligent Systems with Applications · doi:10.1016/j.iswa.2023.200193 · Cited by 21 · see citing works

Facilitating biomedical systematic reviews using ranked text retrieval and classification

Martínez, D., Karimi, S., Cavedon, L., & Baldwin, T. (2008) · Cited by 20 · see citing works

What Will the United States Look Like in 2050? A Chatgpt Short StoryPreprint

McGee, R. W. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4413442 · Cited by 19 · see citing works

PARMOREL: a framework for customizable model repair

Barriga, A., Heldal, R., Rutle, A., & Iovino, L. (2022) · Software & Systems Modeling · doi:10.1007/s10270-022-01005-0 · Cited by 17 · see citing works

Australasian Document Computing Symposium

(2021) · doi:10.1145/3503516 · Cited by 14 · see citing works

Modeling a Tool for Conducting Systematic Reviews Iteratively

Bigendako, B. M., & Syriani, E. (2018) · International Conference on Model-Driven Engineering and Software Development · doi:10.5220/0006664405520559 · Cited by 13 · see citing works

Evaluation and assessment in software engineering 1998

Linkman, S. (1998) · Information and Software Technology · doi:10.1016/s0950-5849(98)00106-2 · Cited by 8 · see citing works

The screening phase in systematic reviews: Can we speed up the process?

Rožanc, I., & Mernik, M. (2021) · Advances in computers · doi:10.1016/bs.adcom.2021.01.006 · Cited by 8 · see citing works

Automated title and abstract screening for scoping reviews using the GPT-4 Large Language ModelPreprint

Wilkins, D. E. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2311.07918 · Cited by 8 · see citing works

Modelling on mobile devices

Brunschwig, L., Guerra, E., & Lara, J. D. (2021) · Software & Systems Modeling · doi:10.1007/s10270-021-00897-8 · Cited by 4 · see citing works

Model-Driven Engineering and Software Development

(2018) · Communications in computer and information science · doi:10.1007/978-3-319-94764-8 · Cited by 3 · see citing works

Deploying AI on Edge: Advancement and Challenges in Edge Intelligence

Wang, T., Guo, J., Zhang, B., Yang, G., & Li, D. (2025) · Mathematics · doi:10.3390/math13111878 · Cited by 92 · see citing works

Enhancing systematic literature reviews with generative artificial intelligence: development, applications, and performance evaluation

Li, Y., Datta, S., Rastegar-Mojarad, M., Lee, K., Paek, H., Glasgow, J., Liston, C., He, L., Wang, X., & Xu, Y. (2025) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaf030 · Cited by 69 · see citing works

Accelerating clinical evidence synthesis with large language models

Wang, Z., Cao, L., Danek, B., Jin, Q., Lu, Z., & Sun, J. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01840-7 · Cited by 69 · see citing works

Critical assessment of large language Models’ (ChatGPT) performance in data extraction for systematic reviews: exploratory study

Mahmoudi, H., Chang, D., Lee, H., Ghaffarzadegan, N., & Jalali, M. S. (2025) · JMIR AI · doi:10.2196/68097 · Cited by 35 · see citing works

Enhancing Clinical Reasoning with Virtual Patients: A Hybrid Systematic Review Combining Human Reviewers and ChatGPT

García-Torres, D., Vicente Ripoll, M. A., Fernández Peris, C., & Mira Solves, J. J. (2024) · Healthcare · doi:10.3390/healthcare12222241 · Cited by 29 · see citing works

A foundation model for human-AI collaboration in medical literature mining

Wang, Z., Cao, L., Jin, Q., Chan, J., Wan, N., Afzali, B., Cho, H.-J., Choi, C.-I., Emamverdi, M., Gill, M. K., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-62058-5 · Cited by 35 · see citing works

Large Language Model for Qualitative Research: A Systematic Mapping Study

Barros, C., Azevedo, B. B., Neto, V. V. G., Kassab, M., Kalinowski, M., do Nascimento, H. A. D., & Bandeira, M. C. G. S. P. (2025) · IEEE/ACM International Workshop on Methodological Issues with Empirical Studies in Software Engineering (WSESE) · doi:10.1109/wsese66602.2025.00015 · Cited by 24 · see citing works

Zero-shot Generative Large Language Models for Systematic Review Screening Automation

Wang, S., Scells, H., Zhuang, S., Potthast, M., Koopman, B., & Zuccon, G. (2024) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-56027-9_25 · Cited by 26 · see citing works

Leveraging open-source large language models (LLMs) in scoping reviews: a case study on disability and AI applications

Bayani, A., Ewane, L. P. E., dos Anjos, D. S. O., Mac-Seing, M., & Nikiema, J. N. (2025) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2025.106048 · Cited by 21 · see citing works

Streamlining evidence based clinical recommendations with large language models

Li, D., Jiang, N., Huang, K., Tu, R., Ouyang, S., Yu, H., Lin, Q., Chen, Y., Zhou, T., Tong, D., et al. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-02273-y · Cited by 20 · see citing works

GAN-Based Data Augmentation for Fault Diagnosis and Prognosis of Rolling Bearings: A Literature Review

Sifat, M. S. I., Kabir, M. A., Islam, M. M. M., Rehman, A. U., & Bermak, A. (2025) · IEEE Access · doi:10.1109/access.2025.3600235 · Cited by 15 · see citing works

Generative artificial intelligence for literature reviews

Wagner, G., Prester, J., Mousavi, R., Lukyanenko, R., & Paré, G. (2026) · Journal of Information Technology · doi:10.1177/02683962261425675 · Cited by 15 · see citing works

On the Utility of Domain Modeling Assistance with Large Language Models

Chaaben, M. B., Burgueño, L., Dávid, I., & Sahraoui, H. A. (2025) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3744920 · Cited by 11 · see citing works

AI-assisted evidence screening method for systematic reviews in environmental research: integrating ChatGPT with domain knowledge

Zuo, C., Yang, X., Errickson, J., Li, J., Hong, Y., & Wang, R. (2025) · Environmental Evidence · doi:10.1186/s13750-025-00358-5 · Cited by 11 · see citing works

The hunt for the last relevant paper: blending the best of humans and AI

van de Schoot, R., Coimbra, B. M., Evenhuis, T., Lombaers, P., Weijdema, F., de Bruin, L., Neeleman, R. C., Grandfield, E. M., Sijbrandij, M., Teijema, J. J., et al. (2025) · European Journal of Psychotraumatology · doi:10.1080/20008066.2025.2546214 · Cited by 10 · see citing works

Large language models for the screening step in systematic reviews in dentistry

Rokhshad, R., Bagherianlemraski, M., Ehsani, S., Haghighat, S., & Schwendicke, F. (2025) · Journal of Dentistry · doi:10.1016/j.jdent.2025.105877 · Cited by 8 · see citing works

Data extraction for systematic mapping study using a large language model - a proof-of-concept study in software engineering

Felizardo, K. R., Steinmacher, I., Lima, M. H. T. D. F., Deizepe, A., Conte, T. U., & Barcellos, M. P. (2024) · Proceedings of the ... ACM-IEEE International Symposium on Empirical Software Engineering and Measurement/International Symposium on Empirical Software Engineering and Measurement · doi:10.1145/3674805.3690743 · Cited by 7 · see citing works

AI Simulation by Digital Twins: Systematic Survey of the State of the Art and a Reference Framework

Liu, X., & Dávid, I. (2024) · ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS) · doi:10.1145/3652620.3688253 · Cited by 7 · see citing works

Pitfalls, benefits, and comparative analysis of artificial intelligence ChatBots in the systematic review process

Daraio, C. C., Leo, S. D., & Ferazzoli, F. (2025) · International Transactions in Operational Research · doi:10.1111/itor.70054 · Cited by 7 · see citing works

Compact large language models for title and abstract screening in systematic reviews: An assessment of feasibility, accuracy, and workload reduction

Sciurti, A., Migliara, G., Siena, L. M., Isonne, C., Blasiis, M. R. D., Sinopoli, A., Iera, J., Marzuillo, C., Vito, C. D., Villari, P., et al. (2025) · Research Synthesis Methods · doi:10.1017/rsm.2025.10044 · Cited by 7 · see citing works

Supporting learners in the transition from block-based to text-based programming, a systematic review

Strong, G., Bresnihan, N., & Tangney, B. (2025) · Journal of Computer Languages · doi:10.1016/j.cola.2025.101342 · Cited by 6 · see citing works

L2D: A Versatile Literature-to-Data set Pipeline for Complex, User-Specific Data Extraction in Environmental Research

Cheng, Y., & Zhang, H. J. (2025) · ACS ES&T Water · doi:10.1021/acsestwater.5c00551 · Cited by 6 · see citing works

On the Difficulties of Conducting and Replicating Systematic Literature Reviews Studies Using LLMs in Software Engineering

Felizardo, K. R., Deizepe, A., COUTINHO, D. J. B., Gomes, G., Meireles, M. A. C., Gerosa, M. A., & Steinmacher, I. (2025) · IEEE/ACM International Workshop on Methodological Issues with Empirical Studies in Software Engineering (WSESE) · doi:10.1109/wsese66602.2025.00010 · Cited by 6 · see citing works

AI simulation by digital twins: systematic survey, reference framework, and mapping to a standardized architecture

Liu, X.-R., & David, I. (2025) · Journal of Software and Systems Modeling · doi:10.1007/s10270-025-01306-0 · Cited by 17 · see citing works

Validating Large Language Models for Title-Abstract Screening in Low-Prevalence Systematic Reviews: An Environmental Science Case Study

Nawrath, M., Merlina, A., Knight, J., Welch, S. A., Rashidian, M., & Seifert-Dähnn, I. (2026) · Information · doi:10.3390/info17050501 · Cited by 6 · see citing works

StudyTypeTeller—Large language models to automatically classify research study types for systematic reviews

Doneva, S. E., de Viragh, S., Hubarava, H., Schandelmaier, S., Briel, M., & Ineichen, B. V. (2025) · Research Synthesis Methods · doi:10.1017/rsm.2025.10031 · Cited by 5 · see citing works

Evaluating the Efficacy and Efficiency of GPT-5 for Automated Title and Abstract Screening in Orthopedic Surgery Systematic Reviews

Vivekanantha, P., Son, H., Bernardini, L., Bouchard, M. D., Ayeni, O. R., & Kay, J. (2025) · Current Reviews in Musculoskeletal Medicine · doi:10.1007/s12178-025-10001-y · Cited by 5 · see citing works

Prompt engineering of large language models for paper screening in medical meta-analyses and systematic reviews: A prospective comparative study.

Adam, T., Abosabie, S. A. S., Dittmer, M., Wolf, E., Abosabie, S., Behnke, C., Baier, F., Weickmann, A., Köser, L., Correll, C., et al. (2026) · Research Synthesis Methods · doi:10.1017/rsm.2026.10093 · Cited by 6 · see citing works

Teaching with intelligence; AI-enhanced pedagogies in nursing education: a scoping review

Nugent, L., Murray, B., Moore, Z., Patton, D., O’Connor, T., Watson, C., Walsh, K., Renjith, V., & George, J. (2026) · Nurse Education in Practice · doi:10.1016/j.nepr.2026.104878 · Cited by 4 · see citing works

Accelerating Disease Model Parameter Extraction: An LLM-Based Ranking Approach to Select Initial Studies for Literature Review Automation

Sujau, M., Wada, M., Vallée, É., Hillis, N., & Sušnjak, T. (2025) · Machine Learning and Knowledge Extraction · doi:10.3390/make7020028 · Cited by 3 · see citing works

A Pilot Study on Generative Artificial Intelligence’s Reliability in Qualitative Research Quality Appraisal Using CASP and JBI Checklists

Shereefdeen, H., Thaivalappil, A., Young, I., & MacKay, M. (2025) · INQUIRY The Journal of Health Care Organization Provision and Financing · doi:10.1177/00469580251399374 · Cited by 3 · see citing works

Cybersecurity in Radio Frequency Technologies: A Scientometric and Systematic Review with Implications for IoT and Wireless Applications

de Araújo, P. R., de Rezende, J. A. M., Faria, D. R. M., & Gomes, O. D. S. M. (2026) · Sensors · doi:10.3390/s26020747 · Cited by 5 · see citing works

Automated systematic reviews using machine learning and large language models in clinical practice guideline development: A perspective

Oami, T., Okada, Y., & Nakada, T. (2026) · Hong Kong Journal of Emergency Medicine · doi:10.1002/hkj2.70085 · Cited by 3 · see citing works

From Bullshit to Cognition

Erslev, M. S., & Tretow-Fish, T. A. B. (2025) · Decennial Aarhus Conference · doi:10.1145/3744169.3744195 · Cited by 2 · see citing works

Large language model enhanced framework for systematic reviews and meta-analyses

Shen, J., Luo, Z., Jia, D., Wang, S., Sun, F., & Wu, J. (2025) · BMJ Digital Health & AI · doi:10.1136/bmjdhai-2025-000017 · Cited by 2 · see citing works

How artificial intelligence shapes customer emotional experiences: a systematic literature review

Lytle, S., & Gopinath, M. (2026) · International Journal of Quality and Service Sciences · doi:10.1108/ijqss-08-2025-0179 · Cited by 2 · see citing works

Goals and strategies for the indexing of publication types and study designs

Smalheiser, N. R., Menke, J. D., Holt, A. W., Halil Kilicoglu, B., & Schneider, J. (2026) · Database · doi:10.1093/database/baag039 · Cited by 2 · see citing works

Using ChatGPT to Evaluate the Methodological Components of Research Proposals: An Experimental Study on Undergraduate English Majors in Vietnam

Tran, T. P., & Nguyen, T. H. L. (2025) · Computer-Assisted Language Learning Electronic Journal · doi:10.54855/callej.252637 · Cited by 1 · see citing works

Harnessing ChatGPT for abstract screening in health-related scoping reviews: the role of structured eligibility criteria

Nordmann, K., & Fischer, F. (2025) · BMC Health Services Research · doi:10.1186/s12913-025-13901-4 · Cited by 1 · see citing works

Can AI be a Scholar? A Systematic Review on the Role of Generative AI in Systematic Literature Reviews

Köhler, J., Harl, M. V., Westner, M. K., & Strahringer, S. (2025) · IEEE Conference on Business Informatics · doi:10.1109/cbi68102.2025.00012 · Cited by 1 · see citing works

Perception–Production of Second-Language Mandarin Tones Based on Interpretable Computational Methods: A Review

Huang, Y., Xu, Z., Bei, X., & Huang, H. (2025) · Mathematics · doi:10.3390/math14010145 · Cited by 1 · see citing works

Balancing rigor and automation: a comparative analysis of Scopus AI and traditional systematic literature reviews

Homer, S. T. (2026) · Quality & Quantity · doi:10.1007/s11135-025-02568-y · Cited by 1 · see citing works

Understanding the Business Intelligence Landscape: A Scientometric Analysis Using Large Language Models

Keenan, P., & Heavin, C. (2026) · Lecture notes in business information processing · doi:10.1007/978-3-032-25146-6_20 · Cited by 1 · see citing works

Workflow-induced evaluation targets in automation-assisted screening: Implications for cumulative evidence in research synthesis

Nunnery, J. A. (2026) · Research Synthesis Methods · doi:10.1017/rsm.2026.10116 · Cited by 1 · see citing works

Collaborative large language models (LLMs) are all you need for screening in systematic reviewsPreprint

Parmar, M., Naqvi, S. A. A., Warraich, K., Saeidi, A., Rawal, S. C., Faisal, K. S., Kazmi, S. Z., Fatima, M., He, H., Safdar, M., et al. (2026) · medRxiv · doi:10.64898/2026.02.07.26345640 · Cited by 1 · see citing works

Reproducible AI-assisted systematic review pipeline applied to digital twins for bridge predictive maintenance and lifecycle management

Musarat, M. A., & Ručevskis, S. (2026) · Automation in Construction · doi:10.1016/j.autcon.2026.107130 · Cited by 1 · see citing works

Machine Learning-Assisted Systematic Review: A Case Study in Learning Analytics

Xu, Z., Zhuang, X., & Ma, S. (2025) · Education Sciences · doi:10.3390/educsci15111488

AIM review tool: artificial intelligence for smarter systematic review screening

Mena, S., Rituerto-González, E., Coutts, F., von Trott, J., Jacobs, G. R., Bryant, L., Moles, L., Sirbu, N., Promet, L., Oliver, D., et al. (2026) · npj Artificial Intelligence · doi:10.1038/s44387-026-00080-8

The Lyme Disease Controversy: An AI-Driven Discourse Analysis of a Quarter Century of Academic Debate and DividesPreprint

Sušnjak, T., Palffy, C., Zimina, T., Altynbekova, N., Garg, K., & Gilbert, L. K. (2025) · medRxiv · doi:10.1101/2025.04.03.25325216

Classification of Randomised Controlled Trial Abstracts by Intervention Type using Zero-Shot and Llama 3 large language models (Preprint)Preprint

Buitrago‐García, D., Courvoisier, D. S., Capderou, S., Iudici, M., & Mongin, D. (2025) · doi:10.2196/preprints.77943

Bridging Oceans: Exploring South America’s Regional Integration Through the Bioceanic Corridor

Vieira, A. D. D. G., da Silva, A. L. R., Frogeri, R. F., Leandro, F. J., & Chen, H. (2025) · Springer eBooks · doi:10.1007/978-981-95-1169-3_28

Brazil and the Geopolitics of Submarine Cables

Bernardino, L. M. B., Frogeri, R. F., & Leandro, F. J. (2025) · Springer eBooks · doi:10.1007/978-981-95-1169-3_27

A Systematic Review of Genes Affecting Endocochlear Potential

Kirwin, D. A., Lewis, M. A., & Steel, K. P. (2026) · Journal of the Association for Research in Otolaryngology · doi:10.1007/s10162-026-01046-y

Recommender Systems for Improving Personalised Research Assistance and Literature Discovery

Ahmad, S., Muhammad, A., Abbas, M. S., & Jan, S. U. (2026) · Engineering Reports · doi:10.1002/eng2.70714

Reporting and Reviewing LLM-Integrated Systems in HCI: Challenges and Considerations

Navarro, K. F., Syriani, E., & Arawjo, I. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790439 · Cited by 1 · see citing works

Eliciting Reader Preferences for Automated Systematic Grey Literature Reviews: A Best-Worst Scaling Study (Preprint)

Ang, Z. Y., Shakirah, M., Lim, W. H., & Lee, S. C. (2026) · JMIR Formative Research · doi:10.2196/97813

A Living Systematic Review Engine: LLM-Automated Evidence Surveillance Validated Against a Published Meta-Analysis of Statins for SepsisPreprint

Farquhar, H. (2026) · Research Square · doi:10.21203/rs.3.rs-9308492/v1

Performance of Zero-Shot Classifiers for Categorizing RCT Abstracts by Intervention Type: Validation Study

Buitrago‐García, D., Courvoisier, D. S., Capderou, S., Iudici, M., & Mongin, D. (2026) · JMIR Medical Informatics · doi:10.2196/77943

Familia-escuela en contextos vulnerables: Prácticas que reducen desigualdades

Hernández, Á. R., Valdivieso, D. L. M., & Prados, M. Á. H. (2026) · Ediciones Comunicación Científica eBooks · doi:10.52501/cc.422.09

Impact of prompt engineering on large language models for risk of bias assessment: a comparative study

Xiong, Y.-T., Wang, Y.-C., Sun, Y., Zhan, Z., Liu, W. T., Liu, H.-N., Meng, R.-Y., Tang, W., & Liu, C. (2026) · BMJ Evidence-Based Medicine · doi:10.1136/bmjebm-2025-114055 · Cited by 1 · see citing works

Using GPT to Classify DSS

Keenan, P. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-21811-7_23

Addressing gender disparities in the efficacy of psychological interventions for behavioral addictions: protocol for a systematic review and individual patient data meta-analysis of randomized controlled trials

Laskowski, N. M., Hambruch, H. R., Zaiser, C., Schnorr, I., Maier, D., Appel, K. S., Vehreschild, J. J., & Paslakis, G. (2026) · Addiction Science & Clinical Practice · doi:10.1186/s13722-026-00668-0

On the Use of a Large Language Model to Support the Conduction of a Systematic Mapping Study: A Brief Report from a Practitioner’s View

Barros, C. F., Kalinowski, M., Kassab, M., & Neto, V. V. G. (2026) · IEEE/ACM International Workshop on Methodological Issues with Empirical Studies in Software Engineering (WSESE) · doi:10.1145/3786149.3788298

Blockchain-Based Data Sharing in the Internet of Vehicles: A Survey

Fan, Y., Guo, Y., Sun, Y., & Zhang, Z. (2026) · Mathematics · doi:10.3390/math14111957

Individual agency and sustainability initiatives in STEM careers and education: a scoping review

Alduais, A. M. S., Tarlochan, F., Chaaban, Y., Mecheter, A., Ibrahim, M. I. M., Elfaki, F. A. M., & Du, X. (2026) · International Journal of STEM Education · doi:10.1186/s40594-026-00626-x

Evaluating a Locally Deployed 20-Billion Parameter Large Language Model for Automated Abstract Screening in Systematic Reviews

Melo, P. H. M., Guadagno, E., & Poenaru, D. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-30813-9_73

Can artificial intelligence accurately assess systematic review quality? Benchmarking large language models for AMSTAR 2 appraisal in dental evidence synthesis

Kurian, N., Cherian, J. M., Reji, R. M., & Varghese, K. G. (2026) · Evidence-Based Dentistry · doi:10.1038/s41432-026-01238-8 · Cited by 1 · see citing works

Researchers' View of Using LLMs in Systematic Literature ReviewsPreprint

dos Santos, V., Lago, P., & Nakagawa, E. Y. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7275147

Reframing workload saving in LLM-assisted screening: A commentary on Sciurti et al.

Lai, H., Liu, J., Ge, L., & Estill, J. (2026) · Research Synthesis Methods · doi:10.1017/rsm.2026.10114

Ensuring trustworthy AI assisted guideline development for clinical practice

Zhang, Q., & Fu, Y. (2026) · npj Digital Medicine · doi:10.1038/s41746-026-03098-z

Automated Data Extraction in Software Engineering SLRs: Promise, Pitfalls, and the Role of Human Oversight

Marco-Pérez, I., Pérez, B., & Rubio, Á. L. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-36587-3_13

The AI Validation Gap in Scientific Knowledge Production

Rahmouni, M. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-8919-6.ch001

Artificial Intelligence and Consumer Well‐Being: A Cross‐Domain Systematic Review

Lytle, S., & Gopinath, M. (2026) · International Journal of Consumer Studies · doi:10.1111/ijcs.70251

Investigación científica en la era de la inteligencia artificial

Pluas, R. E. M., Fernández-Loor, A. O., Mendizábal, V. L. L., Sánchez-Vivanco, J. P., Urbano, A. P. M., & Angulo, R. M. M. (2026) · doi:10.70577/pd8w9r97

An Agentic AI-Aided Review of Large Language Model Applications in Literature Reviews: A Seven-Layer Architecture

Merchán-Cruz, E. A., Gabelaia, I., Soe, S. P., Yatskiv, I., & Dmitry, P. (2026) · Informatics · doi:10.3390/informatics13100160

Real-time and online fatigue assessment of metallic structures: A review and transferability assessment for mobile working machines

Walica, D., Zhidchenko, V., Saeed, S. M., Gupta, T. S., Agúndez, A. G., Härkönen, A., Khadim, Q., Nemov, A. S., Ahola, A., Orzechowski, G., et al. (2026) · Results in Engineering · doi:10.1016/j.rineng.2026.113301

Retrieval-to-abstraction LLM-assisted literature synthesis: Case demonstrations in digital health technology-enabled randomized controlled trial outcome reporting

Harrison, T. B., Hu, D., Jia, H., Tan, S. H., Chen, F., Zhang, Z., Lu, Q., Wang, J., Wang, L., Huang, M., et al. (2026) · PLOS Digital Health · doi:10.1371/journal.pdig.0001768

An Agent-Based Intelligent Literature Analysis Framework for the Taxonomy of Controllable Diffusion-Based Text-to-Video Generation

김민진, Youn, S., 박지예, & Rew, J. (2026) · Journal of Broadcast Engineering · doi:10.5909/jbe.2026.31.5.985

Looking Back, Moving Forward: A Guiding Framework for Future Research in Supply Chain Management

Mecca, D., Patrucco, P. P., Wieland, A., Durach, C. F., Handfield, R., & Nikookar, E. (2026) · Journal of Business Logistics · doi:10.1111/jbl.70098

Reading the Fine Print: Interpreting Performance Claims for AI-Assisted Literature Screening in Higher Education

Nunnery, J. A. (2026) · Journal of Higher Education Theory and Practice · doi:10.33423/5tg2ts54

Zero-To-Few Shot Large Language Model Performance in Systematic Review and Meta-Analysis Automation: A Validation Study Across All Major Steps Of Five Published Systematic ReviewsPreprint

Pietrancosta, M., Wang, S., Wu, Y., Brulotte, V., Harutyunyan, R., Hemmerling, T. M., Morisson, L., & Laferrière-Langlois, P. (2026) · Research Square · doi:10.21203/rs.3.rs-10879359/v1

Mental Health and Psychosocial Processes in Transgender and Gender Diverse Adults with Chronic Physical Illnesses: A Scoping Review

Carvalho, S. A., & Rubio, N. (2026) · Issues in Mental Health Nursing · doi:10.1080/01612840.2026.2739251

An Enhanced Reference Paper Collection System with Generative AI for Paper Relevance Assessment

Fahrudin, T. M., Funabiki, N., Brata, K. C., Kotama, I. N. D., Haz, A. L., Riyantoko, P. A., & Batubulan, K. S. (2026) · Information · doi:10.3390/info17111072

Assessing the Ability of ChatGPT to Screen Articles for Systematic Reviews

Syriani, E., David, I., & Kumar, G. (2023) · arXiv · doi:10.48550/arxiv.2307.06464 · Cited by 27 · see citing works

Large Language Model Demonstrates Human-Comparable Sensitivity in Initial Screening of Systematic Reviews: A Semi-Automated Strategy Using GPT-3.5Preprint

Matsui, K., Utsumi, T., Aoki, Y., Maruki, T., Takeshima, M., & Takaesu, Y. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4520426 · Cited by 7 · see citing works

Methodological insights into ChatGPT’s screening performance in systematic reviews

Issaiy, M., Ghanaati, H., Kolahi, S., Shakiba, M., Jalali, A. H., Zarei, D., Kazemian, S., Avanaki, M. A., & Firouznia, K. (2024) · BMC Medical Research Methodology · doi:10.1186/s12874-024-02203-8 · Cited by 72 · see citing works

Development of Prompt Templates for Large Language Model–Driven Screening in Systematic Reviews

Cao, C., Sang, J., Arora, R., Chen, D., Kloosterman, R., Cecere, M., Gorla, J., Saleh, R., Drennan, I., Teja, B., et al. (2025) · Annals of Internal Medicine · doi:10.7326/annals-24-02189 · Cited by 67 · see citing works

A105 PILOT STUDY ON THE ACCURACY OF CHATGPT IN ARTICLE SCREENING FOR SYSTEMATIC REVIEWS IN GASTROENTEROLOGY

Na, C., Sinanian, G., Gimpaya, N., Mokhtar, A., Chopra, D., Scaffidi, M. A., Yeung, E., & Grover, S. C. (2024) · Journal of the Canadian Association of Gastroenterology · doi:10.1093/jcag/gwad061.105