ArticleBioMed research international2021
An Artificial Neural Networks Model for Early Predicting In-Hospital Mortality in Acute Pancreatitis in MIMIC-III.
Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06124989 (A Novel Machine Learning Model for the Prediction of Relapse of Acute Biliary Pancreatitis), which is not on this map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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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.
A Novel Machine Learning Model for the Prediction of Relapse of Acute Biliary Pancreatitis (Machine learnINg for the rElapse Risk eValuation in Acute Biliary Pancreatitis - MINERVA)
Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.
- A systematic review of machine learning-based prognostic models for acute pancreatitis: Towards improving methods and reporting quality.PLoS medicine · 2025Pooled it
- Machine Learning for Risk Stratification in Acute Pancreatitis: Current Evidence and Future Perspectives.Journal of clinical medicine · 2026Review
- Artificial intelligence in pancreatitis: A narrative review on advancing precision diagnosis, prognosis, and therapeutic strategies.World journal of gastroenterology · 2025Review
- Integrating Feature Selection, Machine Learning, and SHAP Explainability to Predict Severe Acute Pancreatitis.Diagnostics (Basel, Switzerland) · 2025Article
- Machine learning models for predicting in-hospital mortality from acute pancreatitis in intensive care unit.BMC medical informatics and decision making · 2025Article
- Ethical challenges and evolving strategies in the integration of artificial intelligence into clinical practice.PLOS digital health · 2025Article
- AI and Machine Learning for Precision Medicine in Acute Pancreatitis: A Narrative Review.Medicina (Kaunas, Lithuania) · 2025Review
- Construction and validation of risk prediction models for renal replacement therapy in patients with acute pancreatitis.European journal of medical research · 2025Article
- Development and validation of an explainable machine learning model for mortality prediction among patients with infected pancreatic necrosis.EClinicalMedicine · 2025Article
- Lactate dehydrogenase is an indicator for outcomes of short-term and long-term in septic patients.PloS one · 2025Article
- Machine learning predictive model for aspiration risk in early enteral nutrition patients with severe acute pancreatitis.Heliyon · 2024Article
- A deep learning-powered diagnostic model for acute pancreatitis.BMC medical imaging · 2024Article
- Serum Lactate Is an Indicator for Short-Term and Long-Term Mortality in Patients with Acute Pancreatitis.Digestive diseases and sciences · 2024Article
- Advances in the clinical application of machine learning in acute pancreatitis: a review.Frontiers in medicine · 2024Review
- Establishment and Validation of an Early Predictive Model for Severe Acute Pancreatitis.Journal of inflammation research · 2024Article
- Strategies of Predictive Schemes and Clinical Diagnosis for Prognosis Using MIMIC-III: A Systematic Review.Healthcare (Basel, Switzerland) · 2023Review
- Chinese experts' consensus on the application of intensive care big data.Frontiers in medicine · 2023Article
- Early predicting 30-day mortality in sepsis in MIMIC-III by an artificial neural networks model.European journal of medical research · 2022Article
- A prediction model with measured sentiment scores for the risk of in-hospital mortality in acute pancreatitis: a retrospective cohort study.Annals of translational medicine · 2022Article
- EASY-APP: An artificial intelligence model and application for early and easy prediction of severity in acute pancreatitis.Clinical and translational medicine · 2022Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEarly and accurate evaluation of severity and prognosis in acute pancreatitis (AP), especially at the time of admission is very significant. This study was aimed to develop an artificial neural networks (ANN) model for early prediction of in-hospital mortality in AP.
methodsPatients with AP were identified from the Medical Information Mart for Intensive Care-III (MIMIC-III) database. Clinical and laboratory data were utilized to perform a predictive model by back propagation ANN approach.
resultsA total of 337 patients with AP were analyzed in the study, and the in-hospital mortality rate was 11.2%. A total of 12 variables that differed between patients in survivor group and nonsurvivor group were applied to construct ANN model. Three independent variables were identified as risk factors associated with in-hospital mortality by multivariate logistic regression analysis. The predictive performance based on the area under the receiver operating characteristic curve (AUC) was 0.769 for ANN model, 0.607 for logistic regression, 0.652 for Ranson score, and 0.401 for SOFA score.
conclusionAn ANN predictive model for in-hospital mortality in patients with AP in MIMIC-III database was first performed. The patients with high risk of fatal outcome can be screened out easily in the early stage of AP by our model.
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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.