GuidelineNature medicine2020
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension.
Guideline in Nature medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 651 papers, 5 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
651 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- The performance of ChatGPT and other large language models on multiple-choice questions in biomedical disciplines: A meta-analysis.Anatomical sciences education · 2026Pooled it
- Economic evaluations of AI applications in radiology: a systematic review.European radiology · 2026Pooled it
- The Emerging Roles of AI in Self-Directed Stress Management: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Physics-aware imaging AI for quantitative MASLD biomarker mapping: a systematic review of deep learning and radiomics across ultrasound, CT, and MRI.Abdominal radiology (New York) · 2026Pooled it
- Large Language Models in Colorectal Cancer Care and Clinical Decision Support: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Enhancing Asleep Deep Brain Stimulation Targeting for Essential Tremor Using Machine Learning: The OPTIVIM Phase 2 Study.Neurosurgery · 2026Trial
- Generative AI-enabled clinical decision support system in primary care: a pragmatic, cluster-randomized trial.Nature medicine · 2026Trial
- AI-assisted videolaryngoscopy improves intubation success: results from a randomized simulation trial.Journal of clinical monitoring and computing · 2026Trial
- The VALUE of AI-Guided Communication: Enhancing Shared Decision-Making in Metabolic Bariatric Surgery Consultations Through a Metacognitive Framework.Obesity surgery · 2026Trial
- Effect of an electronic health record-integrated machine learning asthma risk marker on pediatrician prognostic accuracy during preschool age: a pilot randomized clinical trial.Scientific reports · 2026Trial
- Hyperbaric oxygen in the artificial intelligence era: integration and innovation.Medical gas research · 2027Review
- Machine Learning in Causal Effect Estimation and Causal Evaluation of ML-Enabled Interventions in Nursing-Related Research: A Scoping Review.Nursing & health sciences · 2026Article
- Dose-conditioned machine-learning prediction of a composite target sedation state in patients undergoing propofol-sedated gastrointestinal endoscopy.Annals of medicine · 2026Observational
- Auditing clinical AI in oncology: Strengthening assurance frameworks and nursing leadership in the Asia-Pacific context.Asia-Pacific journal of oncology nursing · 2026Article
- Artificial intelligence in pediatric nephrology: current applications and emerging frameworks for evidence generation.Pediatric nephrology (Berlin, Germany) · 2026Review
- Toward integrated multimodal artificial intelligence in bone marrow examination: current state and open challenges.Blood research · 2026Review
- From Model to Product: Understanding and Teaching AI Evidence.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2026Article
- Article
- AI-Driven and Automated Systems for Continuous Oxygen Saturation Monitoring in Long-Term Oxygen Therapy: Systematic Review.JMIRx med · 2026Review
- Artificial intelligence in cardiovascular medicine: a practical guide for clinicians and researchers.European heart journal. Digital health · 2026Review
591 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The CONSORT 2010 statement provides minimum guidelines for reporting randomized trials. Its widespread use has been instrumental in ensuring transparency in the evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate impact on health outcomes. The CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trials evaluating interventions with an AI component. It was developed in parallel with its companion statement for clinical trial protocols: SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 29 candidate items, which were assessed by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a two-day consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The CONSORT-AI extension includes 14 new items that were considered sufficiently important for AI interventions that they should be routinely reported in addition to the core CONSORT 2010 items. CONSORT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention is integrated, the handling of inputs and outputs of the AI intervention, the human-AI interaction and provision of an analysis of error cases. CONSORT-AI will help promote transparency and completeness in reporting clinical trials for AI interventions. It will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the quality of clinical trial design and risk of bias in the reported outcomes.
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.