{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T15:26:24Z","timestamp":1773415584863,"version":"3.50.1"},"reference-count":36,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T00:00:00Z","timestamp":1747785600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fundacao para a Ciencia e Tecnologia (FCT)"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>The growing volume of academic publications poses significant challenges for researchers conducting timely and accurate systematic literature reviews (SLR), particularly in fast-evolving fields like artificial intelligence. This growth of academic literature also makes it increasingly difficult for lay people to access scientific knowledge effectively, meaning academic literature is often misrepresented in the popular press and, more broadly, in society. Traditional SLRs are labor-intensive and error-prone, and they struggle to keep up with the rapid pace of new research. To address these issues, we developed PROMPTHEUS: an AI-driven pipeline solution that automates the systematic literature review (LR) process using large language models (LLMs). We aimed to enhance efficiency by reducing the manual workload while maintaining the precision and coherence required for comprehensive literature synthesis. PROMPTHEUS automates key SLR stages, including systematic searches, data extraction, and topic modeling using BERTopic and summarization with transformer models. Evaluations across five research domains demonstrated that PROMPTHEUS reduces review time, achieves high precision, and provides coherent topic organization, offering a scalable and effective solution for conducting literature reviews in an increasingly crowded research landscape.<\/jats:p>","DOI":"10.3390\/info16050420","type":"journal-article","created":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T06:31:27Z","timestamp":1747809087000},"page":"420","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["PROMPTHEUS: A Human-Centered Pipeline to Streamline Systematic Literature Reviews with Large Language Models"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5885-0719","authenticated-orcid":false,"given":"Joao","family":"Torres","sequence":"first","affiliation":[{"name":"INESC-ID, Instituto Superior T\u00e9cnico, Universidade de Lisboa, 1649-004 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3117-9528","authenticated-orcid":false,"given":"Catherine","family":"Mulligan","sequence":"additional","affiliation":[{"name":"SST, Imperial College London, London SW7 2AZ, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5441-4637","authenticated-orcid":false,"given":"Joaquim","family":"Jorge","sequence":"additional","affiliation":[{"name":"INESC-ID, Instituto Superior T\u00e9cnico, Universidade de Lisboa, 1649-004 Lisbon, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8826-5163","authenticated-orcid":false,"given":"Catarina","family":"Moreira","sequence":"additional","affiliation":[{"name":"Data Science Institute, University of Technology Sydney, Ultimo, NSW 2007, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,21]]},"reference":[{"key":"ref_1","unstructured":"Ware, M., and Mabe, M. 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