PRISMA AI reporting guidelines for systematic reviews and meta-analyses on AI in healthcare
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The scoping review was conducted according to the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guideline and the PRISMA-AI extension.
“This scoping review was conducted according to the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guideline [57] and the PRISMA-AI extension [58].”
From Explainability of decoder-only clinical large language models: A scoping review (2026) · cites this paper as [58]
Cites
The PRISMA 2020 statement: an updated guideline for reporting systematic reviews
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Self-citationChecklist for Artificial Intelligence in Medical Imaging (CLAIM): a guide for authors and reviewers
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Self-citationGuidance for Developers of Health Research Reporting Guidelines
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Self-citationLiu, X., Cruz Rivera, S., Moher, D., Calvert, M. J., Denniston, A. K., The SPIRIT-AI and CONSORT-AI Working Group, SPIRIT-AI and CONSORT-AI Steering Group, Chan, A.-W., Darzi, A., Holmes, C., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1034-x · Cited by 1,421 · see citing works
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Self-citationCruz Rivera, S., Liu, X., Chan, A.-W., Denniston, A. K., Calvert, M. J., The SPIRIT-AI and CONSORT-AI Working Group, SPIRIT-AI and CONSORT-AI Steering Group, Darzi, A., Holmes, C., Yau, C., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1037-7 · Cited by 748 · see citing works
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Self-citationReporting guidelines for clinical trials evaluating artificial intelligence interventions are needed
The CONSORT-AI and SPIRIT-AI Steering Group (2019) · Nature Medicine · doi:10.1038/s41591-019-0603-3 · Cited by 143 · see citing works
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Collins, G. S., Moons, K. G. M., Dhiman, P., Riley, R. D., Beam, A. L., Van Calster, B., Ghassemi, M., Liu, X., Reitsma, J. B., van Smeden, M., et al. (2024) · BMJ · doi:10.1136/bmj-2023-078378 · Cited by 4,718 · see citing works
Self-citationArtificial intelligence in surgery
Varghese, C., Harrison, E. M., O’Grady, G., & Topol, E. J. (2024) · Nature Medicine · doi:10.1038/s41591-024-02970-3 · Cited by 287 · see citing works
“…and patients 57 and prioritize compliance with the CONSORT-AI extension 58 , TRIPOD (and its upcoming AI extension) 59,60 , DECIDE-AI 61 and PRISMA AI 62 and other relevant reporting guidelines, to advance the field in a standardized, safe and efficient manner while minimizing research waste.”
Self-citationLiu, T., Krentz, A., Lu, L., & Curcin, V. (2025) · European Heart Journal - Digital Health · doi:10.1093/ehjdh/ztae080 · Cited by 177 · see citing works
Reporting guidelines in medical artificial intelligence: a systematic review and meta-analysis
Kolbinger, F. R., Veldhuizen, G. P., Zhu, J., Truhn, D., & Kather, J. N. (2024) · Communications Medicine · doi:10.1038/s43856-024-00492-0 · Cited by 160 · see citing works
Mechanisms, design, and fabrication strategies for emerging electromagnetic wave-absorbing materials
Chen, G., Li, Z., Zhang, L., Chang, Q., Chen, X., Fan, X., Chen, Q., & Wu, H. (2024) · Cell Reports Physical Science · doi:10.1016/j.xcrp.2024.102097 · Cited by 147 · see citing works
How to optimize the systematic review process using AI tools
Fabiano, N., Gupta, A., Bhambra, N., Luu, B., Wong, S., Maaz, M., Fiedorowicz, J. G., Smith, A. L., & Solmi, M. (2024) · JCPP Advances · doi:10.1002/jcv2.12234 · Cited by 130 · see citing works
“The development of the Preferred Reporting Items for Systematic Reviews and Meta ‐ Analyses AI reporting guidelines in healthcare is currently underway, which will serve to support high ‐ quality, reproducible, and clinically relevant systematic reviews (Cacciamani et al., 2023).”
MethodUsing artificial intelligence for systematic review: the example of elicit
Bernard, N., Sagawa Jr, Y., Bier, N., Lihoreau, T., Pazart, L., & Tannou, T. (2025) · BMC Medical Research Methodology · doi:10.1186/s12874-025-02528-y · Cited by 93 · see citing works
“Finally, the implementation of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) AI reporting guidelines which are currently underway, will be very useful for providing a framework for the use of AI [22].”
Human-AI interaction in skin cancer diagnosis: a systematic review and meta-analysis
Krakowski, I., Kim, J., Cai, Z. R., Daneshjou, R., Lapins, J., Eriksson, H., Lykou, A., & Linos, E. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01031-w · Cited by 87 · see citing works
Artificial intelligence and urology: ethical considerations for urologists and patients
Cacciamani, G. E., Chen, A. W., Gill, I. S., & Hung, A. J. (2023) · Nature Reviews Urology · doi:10.1038/s41585-023-00796-1 · Cited by 67 · see citing works
“Starting in 2019, the EQUATOR Network created a series of guidelines and statements specific for each type of study that would include AI or machine learning as part of the protocol 48–54 , 89 .”
Self-citationSantamato, V., Tricase, C., Faccilongo, N., Iacoviello, M., & Marengo, A. (2024) · Applied Sciences · doi:10.3390/app142210144 · Cited by 67 · see citing works
“Additionally, the need to develop specific guidelines for reporting and evaluating AI in healthcare has been identified, to support systematic reviews and meta-analyses that ensure transparency and reproducibility of results [6].”
Health Care Professionals’ Experience of Using AI: Systematic Review With Narrative Synthesis
Ayorinde, A., Mensah, D. O., Walsh, J., Ghosh, I., Ibrahim, S. A., Hogg, J., Peek, N., & Griffiths, F. (2024) · Journal of Medical Internet Research · doi:10.2196/55766 · Cited by 55 · see citing works
Capacity of ChatGPT to Identify Guideline-Based Treatments for Advanced Solid Tumors
Schulte, B. C. (2023) · Cureus · doi:10.7759/cureus.37938 · Cited by 50 · see citing works
“Leaders within healthcare and technology have sought to assuage these fears, as well as outline means of qualifying abilities of these new tools [2-4].”
BackgroundArtificial Intelligence in Dentistry: A Concise Review of Reporting Checklists and Guidelines
Khurshid, Z., Osathanon, T., Shire, M. A., Schwendicke, F., & Samaranayake, L. P. (2025) · International Dental Journal · doi:10.1016/j.identj.2025.109322 · Cited by 53 · see citing works
“38 They have also been adapted to domain-specific contexts, including dentistry.”
Afzal, M., Li, R. Y. M., Ayyub, M. F., Shoaib, M., & Bilal, M. (2023) · Sustainability · doi:10.3390/su152015117 · Cited by 46 · see citing works
AI, agentic models and lab automation for scientific discovery — the beginning of scAInce
Härtung, T. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1649155 · Cited by 57 · see citing works
Morone, G., De Angelis, L., Martino Cinnera, A., Carbonetti, R., Bisirri, A., Ciancarelli, I., Iosa, M., Negrini, S., Kiekens, C., & Negrini, F. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1550731 · Cited by 41 · see citing works
Williams, M. C., Weir-McCall, J. R., Baldassarre, L. A., Cecco, C. N. D., Choi, A. D., Dey, D., Dweck, M. R., Išgum, I., Kolossváry, M., Leipsic, J. A., et al. (2024) · Journal of cardiovascular computed tomography · doi:10.1016/j.jcct.2024.08.003 · Cited by 38 · see citing works
Xu, C., Wu, F., Du, L., Dong, Y., & Lin, S. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1211399 · Cited by 37 · see citing works
“This meta-analysis was conducted based on PRISMA statements (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) (22, 23).”
MethodWhen and how to disclose AI use in academic publishing: AMEE Guide No.192
Cleland, J., Driessen, E. W., Masters, K., Lingard, L., & Maggio, L. A. (2025) · Medical Teacher · doi:10.1080/0142159x.2025.2607513 · Cited by 44 · see citing works
Kwong, J. C. C., Wu, J., Malik, S., Khondker, A., Gupta, N. K., Bodnariuc, N., Narayana, K., Malik, M., van der Kwast, T., Johnson, A. E. W., et al. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01088-7 · Cited by 35 · see citing works
König, L., Zitzmann, S., Fütterer, T., Campos, D., Scherer, R., & Hecht, M. (2024) · Research Synthesis Methods · doi:10.1002/jrsm.1762 · Cited by 33 · see citing works
“42,43 Several studies have utilized the stopping rule proposed by Ros et al., 24 which involves stopping the AI-AS process after screening n consecutive irrelevant abstracts.”
Nair, A., Ong, W., Lee, A., Leow, N. W., Makmur, A., Ting, Y. H., Lee, Y. J., Ong, S. J., Tan, J. J. H., Kumar, N., et al. (2025) · Diagnostics · doi:10.3390/diagnostics15091146 · Cited by 35 · see citing works
“In parallel, guidelines such as the recent PRISMA extensions for AI research [157] should continue to evolve in step with rapidly expanding AI research and applications.”
(2024) · doi:10.1038/s42256-023-00717-2 · Cited by 30 · see citing works
Self-citationGalli, C., Gavrilova, A. V., & Calciolari, E. (2025) · Information · doi:10.3390/info16050378 · Cited by 36 · see citing works
Ligero, M., Gielen, B., Navarro, V., Morgado, P. C., Prior, O., Dienstmann, R., Nuciforo, P. G., Trebeschi, S., Beets‐Tan, R. G. H., Sala, E., et al. (2024) · npj Precision Oncology · doi:10.1038/s41698-024-00534-9 · Cited by 30 · see citing works
“Efforts are emerging to develop PRISMA-AI guidelines 21 that will de fi ne standardized frameworks, comprehensive method descriptions, and data-sharing practices in radiomics-based studies, as well as, allow study comparison, validation, and meta-analysis efforts in this domain.”
MethodRodler, S., Kidess, M. A., Westhofen, T., Kowalewski, K., BELENCHON, I. R., Taratkin, M. S., Puliatti, S., Rivas, J. G., Veccia, A., Piazza, P., et al. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12165425 · Cited by 25 · see citing works
“Especially for AI-based applications, precise reporting of the algorithm functions will be paramount to facilitate a clear explanation [65].”
BackgroundSelf-citationFleurence, R., Dawoud, D., Bian, J., Higashi, M. K., Wang, X., Xu, H., Chhatwal, J., & Ayer, T. (2025) · Value in Health · doi:10.1016/j.jval.2025.06.018 · Cited by 27 · see citing works
Hasan, S. U., & Siddiqui, M. A. R. (2023) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2023.110943 · Cited by 20 · see citing works
Randomized Controlled Trials Evaluating Artificial Intelligence in Cardiovascular Care
Barzilai, D. H., Sudri, K., Goshen, G., Klang, E., Zimlichman, E., Barbash, I. M., & Cohen, M. S. (2025) · JACC Advances · doi:10.1016/j.jacadv.2025.102152 · Cited by 20 · see citing works
Joshi, S., & Sharma, M. (2023) · Health Systems · doi:10.1080/20476965.2023.2206446 · Cited by 19 · see citing works
“In addition, Review has been performed by authors in accordance with Preferred Reporting Items for Systematic Reviews (PRISMA) standards (Cacciamani et al., 2023).”
MethodBioethical knowledge in students and health professionals: a systematic review
González-Blázquez, F. J., Ruíz-Hontangas, A., & López-Mora, C. (2024) · Frontiers in Medicine · doi:10.3389/fmed.2024.1252386 · Cited by 16 · see citing works
“The methodological process was based on the recommendations presented by the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) statement (107–110).”
MethodKhondker, A., Kwong, J. C. C., Ahmad, I., Rajesh, Z., Dhalla, R., MacNevin, W., Rickard, M., Erdman, L., Gabrielson, A. T., Nguyen, D., et al. (2025) · Journal of Pediatric Urology · doi:10.1016/j.jpurol.2025.01.035 · Cited by 18 · see citing works
Performance measurement systems in primary health care: a systematic literature review
SANTOS, C. J. D. M., Barbosa, A. S., & Sant’Anna, Â. M. O. (2025) · BMC Health Services Research · doi:10.1186/s12913-025-12412-6 · Cited by 23 · see citing works
“PRISMA has been widely endorsed by EQUATOR (Enhancing the Quality and Transparency Of Health Research), promoting reliability and transparency in health services research [47].”
Arzani, S., Karimi, A., Iranmanesh, P., Yazdi, M., Sabeti, M. A., Nekoofar, M. H., Kolahi, J., Bang, H., & Dummer, P. M. H. (2025) · PLoS ONE · doi:10.1371/journal.pone.0329986 · Cited by 16 · see citing works
“…Items for Over-views of Reviews (PRIOR), the Preferred Reporting Items for Systematic reviews and Meta-Analyses of Diagnostic Test Accuracy Studies (PRISMA-DTA) and PRISMA-AI criteria were followed to provide accurate and transparent reporting of the review methodology and results [10–12].”
Khondker, A., Kwong, J. C. C., Rickard, M., Erdman, L., Kim, J. K., Ahmad, I., Weaver, J. K., Fernández, N., Tasian, G. E., Kulkarni, G. S., et al. (2024) · Journal of Pediatric Urology · doi:10.1016/j.jpurol.2024.01.020 · Cited by 16 · see citing works
Rey, R., Gualtieri, R., Scala, G. C. L., & Posfay-Barbe, K. M. (2024) · European Journal of Pediatric Surgery · doi:10.1055/a-2257-5122 · Cited by 16 · see citing works
“37,41 As we speci fi cally examined AI for the diagnosis of appendicitis, our results cannot be extrapolated to other types of AI or other medical conditions.”
Zhang, F., Han, H., Li, M., Tian, T., Zhang, G., Yang, Z., Guo, F., Li, M., Wang, Y., Wang, J., et al. (2025) · Frontiers in Microbiology · doi:10.3389/fmicb.2024.1510026 · Cited by 19 · see citing works
Evaluating artificial intelligence for medical imaging: a primer for clinicians
Keni, S. (2024) · British Journal of Hospital Medicine · doi:10.12968/hmed.2024.0312 · Cited by 15 · see citing works
Arzani, S., Soltani, P., Karimi, A., Yazdi, M., Ayoub, A. F., Khurshid, Z., Galderisi, D., & Devlin, H. (2025) · BMC Medical Imaging · doi:10.1186/s12880-025-01719-9 · Cited by 14 · see citing works
“…methodology and results were reported accurately and transparently by adhering to the Preferred Reporting Items for Overviews of Reviews (PRIOR), the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies (PRISMA-DTA), and PRISMA-AI criteria [20–22].”
Akter, S. B., Akter, S., Tuli, M. D., Eisenberg, D., Lotvola, A., Islam, H., Fresneda, J. E., Hüttemann, M., & Pias, T. S. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.109413 · Cited by 14 · see citing works
Fuellen, G., Kulaga, A. Y., Lobentanzer, S., Unfried, M., Avelar, R. A., Palmer, D. H., & Kennedy, B. K. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102617 · Cited by 15 · see citing works
“On the meta-level, standards for reporting trials of decision support systems driven by AI and for systematic reviews and meta-analyses on AI in healthcare are available or in preparation (Vasey et al., 2022) (Cacciamani et al., 2023).”
Uncovering the sustainability reporting: bibliometric analysis and future research directions
Mishra, P., & Kumar, K. (2023) · International Journal of Disclosure and Governance · doi:10.1057/s41310-023-00216-1 · Cited by 13 · see citing works
“The PRISMA statement is widely used in various academic fields to assist authors in developing high-quality systematic reviews and meta-analyses (Ferenhof et al. 2015; Cacciamani et al. 2023; Nguyen and Nguyen 2023).”
Dermoscopic characteristics of Merkel cell carcinoma
Koumaki, D., Evangelou, G., Katoulis, A., Apalla, Z., Lallas, A., Papadakis, M., Gregoriou, S., Lazaridou, E., & Krasagakis, K. (2024) · BMC Cancer · doi:10.1186/s12885-024-12566-2 · Cited by 13 · see citing works
“The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards were followed for conducting this systematic review with meta-analysis [7].”
MethodReporting standards to support cost-effectiveness evaluations of AI-driven health care
Elvidge, J., & Dawoud, D. (2024) · The Lancet Digital Health · doi:10.1016/s2589-7500(24)00171-7 · Cited by 14 · see citing works
Razak, T. R., Ismail, M. H., Darus, M. Y., Jarimi, H., & Su, Y. (2025) · Research and Reviews in Sustainability · doi:10.5334/rss.6 · Cited by 12 · see citing works
Salybekov, A. A., Wolfien, M., Hahn, W., Hidaka, S., & Kobayashi, S. (2024) · Biomedicines · doi:10.3390/biomedicines12030606 · Cited by 14 · see citing works
“…extension focuses on standardizing the reporting of methods and results for clinical studies using AI, reflecting the most relevant technical details required for future replicability, as well as the clinician’s ability to critically follow and ascertain the relevant outcomes of such studies [64].”
MethodTransitioning from “Dr. Google” to “Dr. ChatGPT”: the advent of artificial intelligence chatbots
Checcucci, E., Rodler, S., Piazza, P., Porpiglia, F., & Cacciamani, G. E. (2024) · Translational Andrology and Urology · doi:10.21037/tau-23-629 · Cited by 12 · see citing works
“Therefore, clear guidelines for use and application are required (20,21).”
Self-citationKale, A. U., Dattani, R., Tabansi, A., Hogg, H. D. J., Pearson, R. V., Glocker, B., Golder, S., Waring, J. J., Liu, X., Moore, D., et al. (2024) · JMIR Research Protocols · doi:10.2196/48156 · Cited by 9 · see citing works
“Reporting of the subsequent review will adhere to the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) reporting guideline for systematic reviews [19] and the PRISMA-AI guideline (if available as this is still in development) [20].”
MethodSelf-citationFrom Data Integration to Precision Medicine: A Value-Based Healthcare Approach for Sarcoma Care
Fuchs, B., & Heesen, P. (2024) · Journal of Clinical Medicine · doi:10.3390/jcm13216500 · Cited by 9 · see citing works
Cai, Z. R., Kim, J., Rezaei, S. J., Chen, M. L., Touma, F., Zhu, C., Onyeka, S., Fonjungo, F., Omiye, J. A., Krakowski, I., et al. (2025) · British Journal of Dermatology · doi:10.1093/bjd/ljaf250 · Cited by 8 · see citing works
“69,70 Additionally, few studies used prospective designs.”
Recent Advances in Electromagnetic Wave Absorbers Fabricated Via Additive Manufacturing
Noh, D., Lim, H., Lee, J., Jang, H., Hong, M., Ji, S., Kang, T., Kang, B., Kim, J., Lee, J., et al. (2025) · International Journal of Precision Engineering and Manufacturing-Green Technology · doi:10.1007/s40684-025-00764-7 · Cited by 8 · see citing works
Chen, Y., Chen, S., & Law, R. (2025) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-07-2024-1033 · Cited by 7 · see citing works
Deep learning in acupuncture: A systematic review
Chen, S., Chen, Y., Yeung, W., Ren, G., Chen, S., Du, H.-X., & Qin, J. (2025) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2025.103300 · Cited by 7 · see citing works
Hassan, A. M., Coert, J. H., Clemens, M. W., Hassanein, A. H., Waljee, J. F., Nelson, J. A., Mehrara, B. J., & Selber, J. C. (2026) · Journal of the American College of Surgeons · doi:10.1097/xcs.0000000000001834 · Cited by 8 · see citing works
Ong, A. Y., Hogg, H. D. J., Kale, A. U., Taribagil, P., Kras, A., Dow, E. R., Macdonald, T., Liu, X., Keane, P. A., & Denniston, A. K. (2024) · JMIR Research Protocols · doi:10.2196/52602 · Cited by 7 · see citing works
“…PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) [19] and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) [20] reporting guidelines, respectively (note that PRISMA-AI [21] is still in development).”
MethodSelf-citationIqbal, Z., Alnuaim, L., Al-Garni, A., Alanzazi, N., AlMukhaylid, S., Qahtani, S. A., Shammas, M. A., Naeem, R. C., Taleb, Y. S., Karrar, T., et al. (2025) · medRxiv · doi:10.1101/2025.07.29.25332402 · Cited by 8 · see citing works
Wu, F., Xu, C., Si, X., He, F., Xu, K., Zhang, Y., & Lin, S. (2025) · Frontiers in Medicine · doi:10.3389/fmed.2024.1477569 · Cited by 6 · see citing works
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
“At the same time, they point to the necessity of evolving ethical frameworks that accompany the deployment of LLMs in research evaluation, moving beyond ad hoc safeguards towards clearer standards for accountability, oversight, and acceptable risk across different applications [59].”
Discapacidad visual e inclusión escolar: una revisión sistemática con PRISMA y VOSviewer
Monge, M. E. T., & Rodríguez, A. (2024) · Ibero-American Journal of Education & Society Research · doi:10.56183/iberoeds.v4i1.649 · Cited by 6 · see citing works
Véras, M. M. S., Pardo, J. P., Lê, M., Jussup, C., Tatmatsu-Rocha, J. C., & Welch, V. A. (2025) · Journal of Personalized Medicine · doi:10.3390/jpm15010029 · Cited by 6 · see citing works
“The results will be reported using PRISMA or PRISMA-AI guidelines if available at the time of reporting [19].”
Nakayama, L., Ribeiro, L. Z., Malerbi, F., & Regatieri, C. (2025) · International Journal of Retina and Vitreous · doi:10.1186/s40942-024-00596-8 · Cited by 11 · see citing works
“Data is the cornerstone upon which AI advancements are built and the description of the included data for algorithm training and of datasets are critical for improving reproducibility and identify possible biases in AI development [9, 10].”
Qureshi, K. N., Nafea, H., & Kim, P. W. (2024) · Expert Systems · doi:10.1111/exsy.13742 · Cited by 5 · see citing works
“The AI models depend on standardization data quality and its training processes (Cacciamani et al., 2023).”
Critical Appraisal Tools for Evaluating Artificial Intelligence in Clinical Studies: Scoping Review
Cabello, J. B., García, V. R., Torralba, M., Fernandez, M. M., Ubeda, M., Ansuategi, E., Ramos-Ruperto, L., Emparanza, J. I., Urreta, I., Iglesias, M. T., et al. (2025) · Journal of Medical Internet Research · doi:10.2196/77110 · Cited by 9 · see citing works
“In 5 cases, the published tool was associated with a systematic review—in some cases developed to create the tool [54], and in others related to the assessment of included studies [24,52].”
König, L., Zitzmann, S., & Hecht, M. (2025) · Research Synthesis Methods · doi:10.1017/rsm.2025.10053 · Cited by 5 · see citing works
“69,70 The findings from this study are expected to support researchers in improving both the efficiency and quality of their literature screening processes when using AI-aided tools such as ASReview.”
Xu, C., Guo, Y., Chen, X., Liu, X., Wu, F., & Lin, S. (2026) · Annals of Medicine · doi:10.1080/07853890.2026.2618431 · Cited by 5 · see citing works
“The meta-analysis was conducted in accordance with the PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) [19,20].”
Self-citationKale, A. U., Hogg, H. D. J., Pearson, R. V., Glocker, B., Golder, S., Coombe, A., Waring, J. J., Liu, X., Moore, D., & Denniston, A. K. (2024) · JMIR Research Protocols · doi:10.2196/51614 · Cited by 5 · see citing works
“Preferred Reporting Items for Systematic Reviews and Meta-Analyses Artificial Intelligence (PRISMA-AI) will be used if published before the submission of this systematic review [29].”
MethodSelf-citationMallardi, D., Maqoud, F., Guido, D., Aloisio, M., Linsalata, M., & Russo, F. (2025) · Nutrients · doi:10.3390/nu17061064 · Cited by 5 · see citing works
Large Language Models in der Wissenschaft
Kowalewski, K., & Rodler, S. (2024) · Die Urologie · doi:10.1007/s00120-024-02396-2 · Cited by 5 · see citing works
Systematic literature review of the use of generative AI in health economic evaluationPreprint
Sharp, S., Lokuge, K., Elvidge, J., Hudson, T., & Dawoud, D. (2025) · medRxiv · doi:10.1101/2025.04.25.25326412 · Cited by 5 · see citing works
Donahue, A. E., Henigman, A., & MacDonald, H. R. (2025) · Journal of Genetic Counseling · doi:10.1002/jgc4.70106 · Cited by 4 · see citing works
“For example, there is a PRISMA AI steering committee currently in the process of “creating an AI implementation of PRISMA guidelines and extensions for studies addressing AI-based interventions” (Blaizot et al., 2022; Cacciamani et al., 2023).”
Bourgeois, J. P., & Ellingson, H. (2025) · Medical Reference Services Quarterly · doi:10.1080/02763869.2025.2537075 · Cited by 6 · see citing works
“12,14,15 Reporting guidelines for systematic reviews are being updated or have been updated to address AI integration into systematic review protocols, 25 though the utilization of AI has required that human experts continually monitor the output to assess accuracy.”
Exploring miRNA Research in Colorectal Cancer: Insights from a Bibliometric Analysis
Piccinno, E., Aloisio, M., Scalavino, V., Russo, F., Giannelli, G., Guido, D., & Serino, G. (2025) · Pharmaceutics · doi:10.3390/pharmaceutics17081084 · Cited by 5 · see citing works
Clinical performance of automated machine learning: a systematic reviewPreprint
Thirunavukarasu, A. J., Elangovan, K., Gutiérrez, L., Hassan, R., Li, Y., Tan, T. F., Cheng, H., Teo, Z. L., Lim, G., & Ting, D. S. W. (2023) · medRxiv · doi:10.1101/2023.10.26.23297599 · Cited by 4 · see citing works
The I-KAPCAM-AI-Q: a novel instrument for evaluating health care providers’ AI awareness in Italy
Cofini, V., Piccardi, L., Benvenuti, E., Pangrazio, G. D., Cimino, E., Mancinelli, M., Muselli, M., Petrucci, E., Picchi, G., Palermo, P., et al. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1655659 · Cited by 3 · see citing works
The nature of sex differences in catecholamine-induced lipolysis in subcutaneous fat cells
Massier, L., Andersson, D. P., Viguerie, N., Zhong, J., Zareifi, D., Kerr, A. G., Langin, D., & Arner, P. (2025) · iScience · doi:10.1016/j.isci.2025.113988 · Cited by 3 · see citing works
AI for dental imaging: impressive in vitro, but what about in practice?
Evans, T., & Hogg, H. D. J. (2025) · Evidence-Based Dentistry · doi:10.1038/s41432-025-01198-5 · Cited by 3 · see citing works
“AI speci fi c reporting guidelines, or extensions are available for many different types of study, however some were published after the included studies were published and gaps in AI-speci fi c guidelines for different study types remain 2,3 .”
Montero, A. M. B., Huet‐Dastarac, M., Herranz-Hernández, S. M., Tengler, B., Buhl, E. S., Galapon, A., Cárdenas, C. E. S., Fusella, M., Herbin, G., de Hond, Y. J. M., et al. (2026) · Physics and Imaging in Radiation Oncology · doi:10.1016/j.phro.2026.100940 · Cited by 3 · see citing works
Co-creation of digital public services through open-source and hybrid platforms: a systematic review
Cuillerier, M., Shiratori, K., Nakashima, M., Therrien, M., & Lawarée, J. (2026) · Asia Pacific Journal of Public Administration · doi:10.1080/23276665.2026.2645560 · Cited by 4 · see citing works
“To ensure methodological transparency and mitigate potential biases linked to using large-language models, this review adopted a standardised protocol aligned with PRISMA-AI guidance (Cacciamani et al., 2023).”
Bozkurt, S., Fereydooni, S., Kar, İ., Chalmers, C. D., Leslie, S., Pathak, R., Walling, A. M., Lindvall, C. J., Lorenz, K., Quest, T. E., et al. (2024) · JMIR Research Protocols · doi:10.2196/56353 · Cited by 3 · see citing works
Zheng, H.-L., Tian, L., & Cai, J.-H. (2024) · Frontiers in Neuroscience · doi:10.3389/fnins.2024.1395639 · Cited by 2 · see citing works
Bravo-Fuentes, P., Jorge, M. A., & Casellas, M. P. L.-P. (2025) · Arts Education Policy Review · doi:10.1080/10632913.2025.2451372 · Cited by 8 · see citing works
“…review of the literature has been carried out, adopting the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol framework (Page et al., 2021) as the organizational model to be followed, which ensures rigor and transparency in the process (Cacciamani et al., 2023).”
Makowska, A., Ananthakrishnan, G., Christ, M., & Dehmer, M. (2025) · Healthcare · doi:10.3390/healthcare13040408 · Cited by 3 · see citing works
“This review’s reporting was guided by the standards of the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) Statement [24].”
Zero-carbon building materials in New Zealand context: a systematic literature review
Araghi, A. H., Rasheed, E. O., Vishnupriya, V., & Seadon, J. (2025) · Discover Applied Sciences · doi:10.1007/s42452-025-06564-7 · Cited by 3 · see citing works
“Adhering to the PRISMA guidelines enhances the quality and reliability of the review, providing a structured framework for the systematic analysis of research findings [53].”
Bowel preparation assessment using artificial intelligence: Systematic review
Cold, K. M., Ali, A., Konge, L., Bjerrum, F., Lovat, L. B., & Ahmad, O. F. (2025) · Endoscopy International Open · doi:10.1055/a-2625-6327 · Cited by 3 · see citing works
Silvestri, C. J., Hoagland, D. L., Woodward, J. M., Naaseh, A., McDermott, C. E., Carter, B. M., Lund, S. B., Prokop, L. J., Bernard, A., & Navarro, S. M. (2025) · Journal of surgical education · doi:10.1016/j.jsurg.2025.103758 · Cited by 2 · see citing works
Sustainability Reporting: A Machine Learning Meta-Regression Analysis
Daovisan, H. (2025) · Technologies · doi:10.3390/technologies14010021 · Cited by 2 · see citing works
“Studies are needed that apply machine learning meta-regression modelling and interpretability to identify latent moderators within the heterogeneous effects of SR across sectors and regions [16].”
Lee, S. Y., Hong, J. S., Lee, S. H., & Gupta, R. (2026) · BMC Medical Research Methodology · doi:10.1186/s12874-026-02825-0 · Cited by 2 · see citing works
Systematic Reviews in the Age of AI: Are We Sacrificing Rigor for Volume?
Ribeiro, H. L., Nepomuceno, F. W. A. B., Pessoa, C. D. Ó., & Gonçalves, M. A. D. A. (2026) · Cochrane Evidence Synthesis and Methods · doi:10.1002/cesm.70080 · Cited by 2 · see citing works
Rodriguez, S., León-Prieto, C., & Rodríguez-Jaime, M. F. (2026) · Journal of Bodywork and Movement Therapies · doi:10.1016/j.jbmt.2026.04.008 · Cited by 2 · see citing works
Reporting Guidelines for Meta‐Analysis in Economics—Updated for AI
Cook, N., Bartos̆, F., Bom, P. R. D., Gechert, S., Kantová, K., Geyer‐Klingeberg, J., Havránek, T., Iršová, Z., Lušková, M., Opatrný, M., et al. (2026) · Journal of Economic Surveys · doi:10.1111/joes.70116 · Cited by 2 · see citing works
Amankwaa, I., Odoom, A., Kasim, A., Kobiah, E., Diebieri, M., Boateng, E. A., Gyamfi, S., & Hales, C. (2026) · Nurse Education Today · doi:10.1016/j.nedt.2026.107154 · Cited by 2 · see citing works
Radócz, L., Nagy, A., Szöllősi, N., Kiss, N. É., Szabó, A., Tamás, J., Siphiwe, N. G., & Radócz, L. (2026) · Remote Sensing · doi:10.3390/rs18132063 · Cited by 2 · see citing works
Challenges of STEM approach in physics learning: A bibliometric analysis
Wıbowo, F. C., Prahanı, B. K., Kurniawan, B. R., Brata, W. W. W., Budhi, H. S., Noor, F. M., Fawaida, U., Jamaludin, D. N., Jalil, M., Ahmad, N. J., et al. (2024) · AIP conference proceedings · doi:10.1063/5.0210180 · Cited by 2 · see citing works
Leveraging Machine Learning for Breast Cancer Prognosis: A Systematic Review
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Artificial Intelligence in Meta-Analysis
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“Moreover, the PRISMA-AI guideline is currently evolving to address the unique challenges associated with conducting systematic reviews in the era of artificial intelligence [2].”
InfluentialLeveraging AI-Driven Health Informatics for Predictive Analytics in Chronic Disease Management
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Ab interno Goniotomy/Goniectomy Techniques
Aktaş, Z., Dorairaj, S. K., Sayed, M. S., Sheybani, A., Üçgül, A. Y., Wagner, I. V., & Khodeiry, M. M. (2025) · Turkish Journal of Ophthalmology · doi:10.4274/tjo.galenos.2025.29345 · Cited by 1 · see citing works
- Authors
- Cacciamani, G. E., Chu, T. N., Sanford, D. I., Abreu, A., Duddalwar, V., Oberai, A., Kuo, C.-C. J., Liu, X., Denniston, A. K., Vasey, B., McCulloch, P., Wolff, R. F., Mallett, S., Mongan, J., Kahn, C. E., Sounderajah, V., Darzi, A., Dahm, P., Moons, K. G. M., Topol, E., Collins, G. S., Moher, D., Gill, I. S., & Hung, A. J.
- Affiliations
- University of Southern California (US)
- University Hospitals Birmingham NHS Foundation Trust (GB)
- University of Oxford (GB)
- Kleijnen Systematic Reviews (United Kingdom) (GB)
- University of California, San Francisco (US)
- University of Pennsylvania (US)
- Imperial College London (GB)
- University of Minnesota (US)
- Utrecht University (NL)
- Scripps Research Institute (US)
- Ottawa Hospital Research Institute (CA)
- Corresponding author
- Cacciamani, Giovanni E.
- ORCID
- Cacciamani, Giovanni E.
- Duddalwar, Vinay
- Oberai, Assad
- Kuo, C.-C. Jay
- Liu, Xiaoxuan
- Denniston, Alastair K.
- Vasey, Baptiste
- McCulloch, Peter
- Wolff, Robert F.
- Mallett, Sue
- Mongan, John
- Kahn, Charles E.
- Sounderajah, Viknesh
- Darzi, Ara
- Dahm, Philipp
- Moons, Karel G. M.
- Topol, Eric
- Collins, Gary S.
- Moher, David
- Gill, Inderbir S.
- Hung, Andrew J.
- Venue
- Nature Medicine
- Published
- 2023-01
- Volume
- 29
- Issue
- 1
- Pages
- 14-15
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W4316507599
- Cited by
- 143
- References
- 10
- Citations by year
- 2026: 42 · 2025: 50 · 2024: 42 · 2023: 9
- FWCI
- 8.88
- Type
- journal article
- Language
- en
- Open access
- green
- discovery.ucl.ac.uk
- Licence
- Locations
- Nature Medicine (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion, other-oa)
- Funders
- Alan Turing Institute (TU/ASG/R-SPEH-113)
- Cancer Research UK (27294)
- National Institute for Health and Care Research (NIHR205103, NF-SI-0510-10186, NF-SI-0617-10038)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
- Keywords
- reporting guidelines, artificial intelligence in healthcare, systematic reviews, meta-analysis
- MeSH terms
- Artificial Intelligence, Delivery of Health Care, Publishing, Checklist
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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