ArticleFrontiers in medicine2020
A Machine Learning-Based Prediction of Hospital Mortality in Patients With Postoperative Sepsis.
Article in Frontiers in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 3 of them syntheses 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
44 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- AI-Based Sepsis Prediction in Hospitalized Adults: Systematic Review, Subgroup Meta-Analysis, and Contextual Analysis of Clinical Burden.Journal of medical Internet research · 2026Pooled it
- Sepsis mortality prediction using machine learning and deep learning - a systematic review.BMC medical informatics and decision making · 2025Pooled it
- Machine learning for the prediction of sepsis-related death: a systematic review and meta-analysis.BMC medical informatics and decision making · 2023Pooled it
- Prediction of death in burn patients infected with antibiotic-resistant Staphylococcus aureus using machine learning based techniques.BMC infectious diseases · 2026Article
- Development of an interpretable machine learning model for predicting in-hospital mortality in ICU patients with sepsis: a retrospective cohort study.Frontiers in medicine · 2026Article
- Machine learning for prediction of in-ICU mortality in sepsis: an observational study using the MIMIC IV database.Archives of medical science : AMS · 2026Article
- Predicting Agitation-Sedation Levels in Intensive Care Unit Patients: Development of an Ensemble Model.JMIR medical informatics · 2025Article
- Construction and verification of a nomogram model for the risk of death in sepsis patients.Scientific reports · 2025Article
- An interpretable machine learning model for predicting in-hospital mortality in ICU patients with ventilator-associated pneumonia.PloS one · 2025Article
- Survival analysis of antibiotics in patients undergoing cardiopulmonary bypass in the intensive care unit: a study based on the Medical Information Mart for Intensive Care-IV database.Archives of medical science : AMS · 2025Article
- Interpretable Machine Learning Model for Early Mortality Prediction in Septic Patients Using Routine Post-Diagnosis Clinical Data: A Multicenter Study.Journal of inflammation research · 2025Article
- Postoperative sepsis-associated neurocognitive disorder: mechanisms, predictive strategies, and treatment approaches.Frontiers in medicine · 2025Review
- Machine learning application for prediction of surgical site infection after posterior cervical surgery.International wound journal · 2024Article
- Predicting sepsis in-hospital mortality with machine learning: a multi-center study using clinical and inflammatory biomarkers.European journal of medical research · 2024Article
- A predictive model for postoperative adverse outcomes following surgical treatment of acute type A aortic dissection based on machine learning.Journal of clinical hypertension (Greenwich, Conn.) · 2024Article
- Early Prediction of Mortality for Septic Patients Visiting Emergency Room Based on Explainable Machine Learning: A Real-World Multicenter Study.Journal of Korean medical science · 2024Article
- Deep learning-based prediction of in-hospital mortality for sepsis.Scientific reports · 2024Article
- Article
- A machine learning-based prediction of hospital mortality in mechanically ventilated ICU patients.PloS one · 2024Article
- Machine learning prognosis model based on patient-reported outcomes for chronic heart failure patients after discharge.Health and quality of life outcomes · 2023Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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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.