ArticleClinics (Sao Paulo, Brazil)2023
Early prediction of acute respiratory distress syndrome complicated by acute pancreatitis based on four machine learning models.
Article in Clinics (Sao Paulo, Brazil), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 6 of them syntheses that pooled it.
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Who cites it
20 citing papers in PubMed, 6 syntheses or guidelines pooled it, 27 citations in OpenAlex.
- Incidence and factors independently associated with acute respiratory distress syndrome in chinese patients with severe acute pancreatitis: a systematic review and meta-analysis.BMC pulmonary medicine · 2026Pooled it
- Prediction models for the occurrence and mortality of sepsis-associated lung injury: a systematic review and meta-analysis.Frontiers in medicine · 2026Pooled it
- Predictive Modeling of Acute Respiratory Distress Syndrome Using Machine Learning: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- A systematic review of machine learning-based prognostic models for acute pancreatitis: Towards improving methods and reporting quality.PLoS medicine · 2025Pooled it
- Accuracy of artificial intelligence algorithms in predicting acute respiratory distress syndrome: a systematic review and meta-analysis.BMC medical informatics and decision making · 2025Pooled it
- A systematic review of machine learning models for management, prediction and classification of ARDS.Respiratory research · 2024Pooled it
- Machine learning in ARDS: an intensivist's guide to artificial intelligence applications.Critical care (London, England) · 2026Review
- A Clinical Data-Based Nomogram Prediction Model for ARDS in Patients With Acute Pancreatitis.International journal of general medicine · 2026Article
- Concentration and predictive value of plasma neutrophil gelatinase-associated lipocalin in patients with acute pancreatitis and acute kidney injury.World journal of nephrology · 2025Article
- Early Prediction of Acute Respiratory Distress Syndrome in Critically Ill Polytrauma Patients Using Balanced Random Forest ML: A Retrospective Cohort Study.Journal of clinical medicine · 2025Article
- An early predictive model for acute respiratory distress-syndrome related to pancreatitis in pregnancy: an 8-year multicenter analysis.European journal of medical research · 2025Article
- AI and Machine Learning for Precision Medicine in Acute Pancreatitis: A Narrative Review.Medicina (Kaunas, Lithuania) · 2025Review
- Acute respiratory distress syndrome (ARDS): from mechanistic insights to therapeutic strategies.MedComm · 2025Review
- Clinical Use of Nomogram Based on Machine Learning for Diagnosis Prediction of Acute Respiratory Distress Syndrome in Patients With Acute Pancreatitis.Mediators of inflammation · 2025Article
- Triglyceride-glucose index as a key predictor of ARDS in acute pancreatitis: SHAP analysis reveals its critical role in risk stratification.Frontiers in nutrition · 2025Article
- Predicting the risk of early intensive care unit admission for patients hospitalized with acute pancreatitis using supervised machine learning.Proceedings (Baylor University. Medical Center) · 2024Article
- Advances in the clinical application of machine learning in acute pancreatitis: a review.Frontiers in medicine · 2024Review
- Acute pancreatitis: A review of diagnosis, severity prediction and prognosis assessment from imaging technology, scoring system and artificial intelligence.World journal of gastroenterology · 2023Review
- Protective effect of rivastigmine against lung injury in acute pancreatitis model in rats via Hsp 70/IL6/ NF-κB signaling cascade.International journal of immunopathology and pharmacologyArticle
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Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAcute Respiratory Distress syndrome (ARDS) is a common complication of Acute Pancreatitis (AP) and is associated with high mortality. This study used Machine Learning (ML) to predict ARDS in patients with AP at admission.
methodsThe authors retrospectively analyzed the data from patients with AP from January 2017 to August 2022. Clinical and laboratory parameters with significant differences between patients with and without ARDS were screened by univariate analysis. Then, Support Vector Machine (SVM), Ensembles of Decision Trees (EDTs), Bayesian Classifier (BC), and nomogram models were constructed and optimized after feature screening based on these parameters. Five-fold cross-validation was used to train each model. A test set was used to evaluate the predictive performance of the four models.
resultsA total of 83 (18.04%) of 460 patients with AP developed ARDS. Thirty-one features with significant differences between the groups with and without ARDS in the training set were used for modeling. The Partial Pressure of Oxygen (PaO
conclusionsA predictive model of ARDS complicated by AP was successfully developed based on ML. Predictive performance was evaluated by a test set, for which BC showed superior predictive performance and EDTs could be a more promising prediction tool for larger samples.
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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.