ArticleNature medicine2020
Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist.
Abstract read
In one paragraph
Article in Nature medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 294 papers, 14 of them syntheses that pooled it.
0numbers the graph read from it
0cells of the map it votes in
294citing papers in PubMed, 14 pooled it
–field-weighted citation impact
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
294 citing papers in PubMed, 14 syntheses or guidelines pooled it.
- Artificial intelligence in nongynecologic cytology: A systematic review of current research and commercial tools.Cancer cytopathology · 2026Pooled it
- Digital technologies and clinical decision support tools available for diabetes triage in the inpatient setting: A systematic literature review.Diabetic medicine : a journal of the British Diabetic Association · 2026Pooled it
- Pooled it
- The TRIPOD-LLM reporting guideline for studies using large language models: a Korean translation.Ewha medical journal · 2025Guideline
- TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods: a Korean translation.Ewha medical journal · 2025Guideline
- Adherence of studies involving artificial intelligence in the analysis of ophthalmology electronic medical records to AI-specific items from the CONSORT-AI guideline: a systematic review.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2024Pooled it
- Machine learning models including patient-reported outcome data in oncology: a systematic literature review and analysis of their reporting quality.Journal of patient-reported outcomes · 2024Pooled it
- AI Quality Standards in Health Care: Rapid Umbrella Review.Journal of medical Internet research · 2024Pooled it
- Artificial intelligence in the risk prediction models of cardiovascular disease and development of an independent validation screening tool: a systematic review.BMC medicine · 2024Pooled it
- Artificial intelligence in endoscopy related to inflammatory bowel disease: A systematic review.Indian journal of gastroenterology : official journal of the Indian Society of Gastroenterology · 2024Pooled it
- The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Using machine learning methods to predict all-cause somatic hospitalizations in adults: A systematic review.PloS one · 2024Pooled it
- The endorsement of general and artificial intelligence reporting guidelines in radiological journals: a meta-research study.BMC medical research methodology · 2023Pooled it
- APPRAISE-AI Tool for Quantitative Evaluation of AI Studies for Clinical Decision Support.JAMA network open · 2023Pooled it
- Consumer wearable devices for evaluation of heart rate control using digoxin versus beta-blockers: the RATE-AF randomized trial.Nature medicine · 2024Trial
- Artificial intelligence in central nervous system autoimmune diseases: from clinical decision support to mechanistic discovery and translation.EMBO molecular medicine · 2026Review
- Review
- Artificial Intelligence in Photodynamic Therapy: From Molecular Design of Photosensitizers to Intelligent Delivery, Adaptive Dosimetry, and Personalized Prognostication of Results.International journal of molecular sciences · 2026Review
- Artificial intelligence in biomarker discovery for diseases: diagnostic and therapeutic prospects.Signal transduction and targeted therapy · 2026Review
- Machine perfusion distribution across clinical phenotypes in kidney transplantation: A national cohort study using unsupervised clustering.World journal of transplantation · 2026Article
234 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
13 authors.
Beau NorgeotBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
Giorgio QuerScripps Research Translational Institute, San Diego, CA, USA.ORCID http://orcid.org/0000-0003-2208-7912
Brett K Beaulieu-JonesDepartment of Biomedical Informatics, Boston, MA, USA.
Ali TorkamaniScripps Research Translational Institute, San Diego, CA, USA.ORCID http://orcid.org/0000-0003-0232-8053
Raquel DiasScripps Research Translational Institute, San Diego, CA, USA.
Milena GianfrancescoDivision of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
Rima ArnaoutBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
Isaac S KohaneDepartment of Biomedical Informatics, Boston, MA, USA.
Suchi SariaDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
Eric TopolScripps Research Translational Institute, San Diego, CA, USA.ORCID http://orcid.org/0000-0002-1478-4729
Ziad ObermeyerDivision of Health Policy and Management, School of Public Health, University of California at Berkeley, Berkeley, CA, USA.
Bin YuDepartment of Statistics and Department of Electrical Engineering & Computer Science, University of California at Berkeley, Berkeley, CA, USA.
Atul J ButteBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA. atul.butte@ucsf.edu.ORCID http://orcid.org/0000-0002-7433-2740
Funding
Toward efficient performance for deep learning on medical imagingR01HL150394 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Rima Arnaout · 2020 to 2026
$6.2MGenetics and Structure of Trabecular Myocardium in Development and DiseaseK08HL125945 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ARNAOUT, RIMA · 2015 to 2019
$863kComputational methods using electronic health records and registry data to detect and predict clinical outcomes in rheumatic diseaseK01AR075085 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GIANFRANCESCO, MILENA ANNE · 2019 to 2022
$458kNHLBI NIH HHS K08 HL125945NHLBI NIH HHS R01 HL150394NIAMS NIH HHS K01 AR075085
Abstract
PubMed holds no abstract for this paper.
Indexed as
Artificial IntelligenceArthritis, RheumatoidDiabetic RetinopathyDrug-Related Side Effects and Adverse ReactionsHumansMachine Learning
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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.