ArticleNature machine intelligence2022
Generalizability of an acute kidney injury prediction model across health systems.
Article in Nature machine intelligence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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
26 citing papers in PubMed, 43 citations in OpenAlex.
- Development and validation of an early prediction model for bee-sting-induced acute kidney injury using machine learning.Renal failure · 2026Article
- Using classification and regression trees (CART) to investigate unknown ethnicity records in NHS emergency care data.BMJ open · 2026Article
- Discovery of postoperative clinical states linked to cardiac surgery-associated acute kidney injury.BioData mining · 2026Article
- Exploring the limits of localization: federated model stacking improves hospital-level prediction in a national research network.NPJ digital medicine · 2026Article
- The health and care workforce crisis: co-benefits of gender-transformative approaches and capacities for implementation.European journal of public health · 2026Article
- Forecasting ICU Acute Kidney Injury with Actionable Lead Time Using Interpretable Machine Learning: Development and Multi-Center Validation.Journal of clinical medicine · 2026Article
- Predicting Acute Kidney Injury with Nephrotoxic Burden in Noncritical Patients: An Internal and External Validation Study.Kidney360 · 2026Article
- Challenges and Solutions in Applying Large Language Models to Guideline-Based Management Planning and Automated Medical Coding in Health Care: Algorithm Development and Validation.JMIR biomedical engineering · 2025Article
- Developing machine learning-driven acute kidney injury predictive models using non-standard EMRs in resource-limited settings.Medical physics · 2025Observational
- Multicenter validation of a scalable, interpretable, multitask prediction model for multiple clinical outcomes.NPJ digital medicine · 2025Article
- Review
- Multicenter Validation of a Machine Learning Model for Surgical Transfusion Risk at 45 US Hospitals.JAMA network open · 2025Article
- Health Equity and Artificial Intelligence in Nephrology.Clinical journal of the American Society of Nephrology : CJASN · 2025Article
- A Review of Leveraging Artificial Intelligence to Predict Persistent Postoperative Opioid Use and Opioid Use Disorder and its Ethical Considerations.Current pain and headache reports · 2025Review
- Assessments of Generative Artificial Intelligence as Clinical Decision Support Ought to be Incorporated Into Randomized Controlled Trials of Electronic Alerts for Acute Kidney Injury.Mayo Clinic proceedings. Digital health · 2024Review
- Performance of Machine Learning Suicide Risk Models in an American Indian Population.JAMA network open · 2024Article
- Development and Validation of a Machine Learning COVID-19 Veteran (COVet) Deterioration Risk Score.Critical care explorations · 2024Article
- An empirical study on KDIGO-defined acute kidney injury prediction in the intensive care unit.Bioinformatics (Oxford, England) · 2024Article
- Towards global model generalizability: independent cross-site feature evaluation for patient-level risk prediction models using the OHDSI network.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management.Cell metabolism · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
Delays in the identification of acute kidney injury (AKI) in hospitalized patients are a major barrier to the development of effective interventions to treat AKI. A recent study by Tomasev and colleagues at DeepMind described a model that achieved a state-of-the-art performance in predicting AKI up to 48 hours in advance.
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.