ArticleFrontiers in medicine2021
Application of Machine Learning to Predict Acute Kidney Disease in Patients With Sepsis Associated Acute Kidney Injury.
Article in Frontiers in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.
- Validated risk prediction models for outcomes of acute kidney injury: a systematic review.BMC nephrology · 2023Pooled it
- Early recognition of sepsis-associated acute kidney injury based on BioBERT-BPNN multimodal clinical data analysis.PloS one · 2026Article
- Risk prediction for acute kidney disease and adverse outcomes in patients with chronic obstructive pulmonary disease: an interpretable machine learning approach.Renal failure · 2025Article
- Enhancing mortality prediction in intensive care units: improving APACHE II, SOFA, and SAPS II scoring systems using long short-term memory.Internal and emergency medicine · 2025Article
- Identification of Key Genes and Potential Therapeutic Targets in Sepsis-Associated Acute Kidney Injury Using Transformer and Machine Learning Approaches.Bioengineering (Basel, Switzerland) · 2025Article
- Machine Learning to Assist in Managing Acute Kidney Injury in General Wards: Multicenter Retrospective Study.Journal of medical Internet research · 2025Article
- Article
- Transforming critical care: the digital revolution's impact on intensive care units.Frontiers in digital health · 2025Review
- Acute Kidney Injury Prognosis Prediction Using Machine Learning Methods: A Systematic Review.Kidney medicine · 2025Review
- Predictive models of sepsis-associated acute kidney injury based on machine learning: a scoping review.Renal failure · 2024Article
- A machine learning-based approach for predicting renal function recovery in general ward patients with acute kidney injury.Kidney research and clinical practice · 2024Article
- Artificial intelligence and machine learning's role in sepsis-associated acute kidney injury.Kidney research and clinical practice · 2024Article
- Machine Learning for Predicting Risk and Prognosis of Acute Kidney Disease in Critically Ill Elderly Patients During Hospitalization: Internet-Based and Interpretable Model Study.Journal of medical Internet research · 2024Article
- Acute Kidney Injury Prediction Model Using Cystatin-C, Beta-2 Microglobulin, and Neutrophil Gelatinase-Associated Lipocalin Biomarker in Sepsis Patients.International journal of nephrology and renovascular disease · 2024Article
- Correlation between neutrophil-to-lymphocyte ratio and contrast-induced acute kidney injury and the establishment of machine-learning-based predictive models.Renal failure · 2023Article
- Machine learning for the prediction of all-cause mortality in patients with sepsis-associated acute kidney injury during hospitalization.Frontiers in immunology · 2023Article
- Development and deployment of interpretable machine-learning model for predicting in-hospital mortality in elderly patients with acute kidney disease.Renal failure · 2022Article
- Machine Learning for Acute Kidney Injury Prediction in the Intensive Care Unit.Advances in chronic kidney disease · 2022Review
- Predictors of Acute Kidney Disease Severity in Hospitalized Patients with Acute Kidney Injury.Biomedicines · 2022Article
- Machine Learning and Antibiotic Management.Antibiotics (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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.