ReviewJCPP advances2024
How to optimize the systematic review process using AI tools.
Review in JCPP advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
37 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Identifying and Prioritizing Core Components of Relationship Education Programs: a Case Study of an Artificial Intelligence (AI) Assisted Systematic Review.Prevention science : the official journal of the Society for Prevention Research · 2026Pooled it
- Psychosocial responses to outdoor artificial light at night (ALAN): a scoping review.Frontiers in psychology · 2026Pooled it
- Evaluation of a large language model (ChatGPT) versus human researchers in assessing risk-of-bias and community engagement levels: a systematic review use-case analysis.European journal of public health · 2025Pooled it
- The effectiveness and perceived value of feedback used in cardiac arrest simulation education: a mixed-method systematic review.Scandinavian journal of trauma, resuscitation and emergency medicine · 2025Pooled it
- Reproducible study identification and selection in systematic reviews: barriers and paths forward.BMJ open · 2026Article
- Comparative performance of large language models for appraising bias in real-world evidence studies.Journal of managed care & specialty pharmacy · 2026Article
- Transforming Systematic Reviews: Evaluating a Fine-Tuned Large Language Model for Abstract Screening in Uveitis and Retinal Vasculitis: Fine-Tuned LLM for Review Screening.Ophthalmology science · 2026Article
- Comparative evaluation of artificial intelligence-assisted literature search tools for identifying clinically meaningful evidence in cardiology.European heart journal. Digital health · 2026Article
- Large language models vs. conventional search in identifying delirium guidelines for a scoping review.BMC medical research methodology · 2026Article
- Clinical research on homeopathic preparations: protocol template for a series of systematic reviews.Systematic reviews · 2026Article
- Artificial Intelligence in Health Professions Education: Qualitative Study of Student Experiences.Journal of medical Internet research · 2026Article
- AI-Assisted Systematic Review: Humans Still Need to Review All Abstracts for Inclusion.JMIR formative research · 2026Article
- The Promise of Artificial Intelligence to Aid in Systematic Reviews: An Examination of Scopus AI.Journal of the advanced practitioner in oncology · 2026Article
- Disclosing artificial intelligence use in scientific research and publication: When should disclosure be mandatory, optional, or unnecessary?Accountability in research · 2026Article
- A pathway-informed mutual exclusivity framework to detect genetic interactions in pediatric cancer.BMC medical genomics · 2025Article
- Artificial intelligence in orthopedic research assistance: a resident's perspective.Musculoskeletal surgery · 2025Review
- Protocol: Understanding the Content, Context, and Impact of Far-Right Extremist Propaganda Disseminated Online: A Systematic Review.Campbell systematic reviews · 2025Article
- Common features of rare disease patients in the emergency department: a systematised literature review.Orphanet journal of rare diseases · 2025Review
- Artificial intelligence as team member versus manual screening to conduct systematic reviews in medical sciences.iScience · 2025Article
- The introduction and adoption of artificial intelligence in systematic literature reviews: a discrete choice experiment.BMJ open · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Systematic reviews are a cornerstone for synthesizing the available evidence on a given topic. They simultaneously allow for gaps in the literature to be identified and provide direction for future research. However, due to the ever-increasing volume and complexity of the available literature, traditional methods for conducting systematic reviews are less efficient and more time-consuming. Numerous artificial intelligence (AI) tools are being released with the potential to optimize efficiency in academic writing and assist with various stages of the systematic review process including developing and refining search strategies, screening titles and abstracts for inclusion or exclusion criteria, extracting essential data from studies and summarizing findings. Therefore, in this article we provide an overview of the currently available tools and how they can be incorporated into the systematic review process to improve efficiency and quality of research synthesis. We emphasize that authors must report all AI tools that have been used at each stage to ensure replicability as part of reporting in methods.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.