Research graph
References from Development of interpretable machine learning models for predicting the probability of sepsis in patients with pulmonary fibrosis in the intensive care unit: based on MIMIC-IV and multi-database validation. Local targets link to admitted publications; unresolved targets remain external evidence.
Managing acute exacerbations in idiopathic pulmonary fibrosis and progressive pulmonary fibrosis in the intensive care unit setting
10.1016/j.cnc.2025.05.002 · 2025 · External reference
Early corticosteroid dose tapering in patients with acute exacerbation of idiopathic pulmonary fibrosis
10.1186/s12931-022-02195-3 · 2022 · External reference
Advanced meta-ensemble machine learning models for early and accurate sepsis prediction to improve patient outcomes
10.48550/arxiv.2407.08107 · 2024 · External reference
Risk of subsequent sepsis within 90 days after a hospital stay by type of antibiotic exposure
10.1093/cid/cix947 · 2018 · External reference
Early palliative care program in idiopathic pulmonary fibrosis patients favors at-home and hospice deaths, reduces unplanned medical visits, and prolongs survival: A pilot study
10.1016/j.ejim.2024.05.024 · 2024 · External reference
XGBoost: A scalable tree boosting system. In:
2016 · External reference
Support-vector networks
10.1007/bf00994018 · 1995 · External reference
Logistic regression and artificial neural network classification models: a methodology review
10.1016/s1532-0464(03)00034-0 · 2002 · External reference
Acute exacerbation of IPF has systemic consequences with multiple organ injury, with SRA(+) and TNF-α(+) cells in the systemic circulation playing central roles in multiple organ injury
10.1186/s12890-016-0298-x · 2016 · External reference
Pulmonary complications after acute kidney injury
10.1053/j.ackd.2008.04.008 · 2008 · External reference
Neural network-based surrogate modeling and optimization of a multigeneration system
10.1016/j.apenergy.2024.123130 · 2024 · External reference
Fine-tuning pre-trained networks with emphasis on image segmentation: a multi-network approach for enhanced breast cancer detection
10.1016/j.engappai.2024.109666 · 2025 · External reference
Incidence and prevalence of idiopathic pulmonary fibrosis: a systematic literature review and meta-analysis
10.1186/s12890-025-03836-1 · 2025 · External reference
PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals
10.1161/01.cir.101.23.e215 · 2000 · External reference
Dementia and the risk of short-term readmission and mortality after a pneumonia admission
10.1371/journal.pone.0246153 · 2021 · External reference
Prognostic significance of red cell distribution width in idiopathic pulmonary fibrosis and combined pulmonary fibrosis emphysema
10.1159/000511106 · 2021 · External reference
Global epidemiology and outcomes of acute kidney injury
10.1038/s41581-018-0052-0 · 2018 · External reference
MIMIC-IV, a freely accessible electronic health record dataset
10.1038/s41597-022-01899-x · 2023 · External reference
Management of patients with idiopathic pulmonary fibrosis and lung cancer: challenges in clinical practice
10.1097/mcp.0000000000000977 · 2023 · External reference
LightGBM: a highly efficient gradient boosting decision tree
2017 · External reference
Skin cancer diagnosis (SCD) using artificial neural network (ANN) and improved gray wolf optimization (IGWO)
10.1038/s41598-023-45039-w · 2023 · External reference
The burden of sepsis and septic shock in the intensive care unit
10.3390/jcm14196691 · 2025 · External reference
Classification and regression tree analysis in public health: methodological review and comparison with logistic regression
10.1207/s15324796abm2603_02 · 2003 · External reference
Comparing artificial intelligence and traditional regression models in lung cancer risk prediction using a systematic review and meta-analysis
10.1016/j.jacr.2025.02.042 · 2025 · External reference
Correlation between red cell distribution width to total calcium ratio and in-hospital mortality in patients with non-idiopathic pulmonary fibrosis interstitial lung diseases: a retrospective cohort study from the MIMIC-IV database
10.1097/md.0000000000047560 · 2026 · External reference
Explainable AI: a review of machine learning interpretability methods
10.3390/e23010018 · 2020 · External reference
The evolution of artificial intelligence in nuclear medicine
10.1053/j.semnuclmed.2025.01.006 · 2025 · External reference
Machine learning for the prediction of mortality in patients with sepsis-associated acute kidney injury: a systematic review and meta-analysis
10.1186/s12879-024-10380-6 · 2024 · External reference
The reliability of lung ultrasound in assessment of idiopathic pulmonary fibrosis
10.2147/cia.s156615 · 2018 · External reference
Th17 cells contribute to pulmonary fibrosis and inflammation during chronic kidney disease progression after acute ischemia
10.1152/ajpregu.00147.2017 · 2018 · External reference
Neurocognitive impairment in idiopathic pulmonary fibrosis: a systematic review of current evidence
10.3390/medsci13040288 · 2025 · External reference
Outcomes of patients with acute exacerbations of idiopathic pulmonary fibrosis treated with corticosteroids: a systematic review and meta-analysis
10.1186/s12931-026-03648-9 · 2026 · External reference
Differences in disease characteristics and outcomes as determined by biological sex in a large UK idiopathic pulmonary fibrosis population: analysis from the British Thoracic Society, Interstitial Lung Disease registry data
10.1136/bmjresp-2025-003301 · 2025 · External reference
Global, regional, and national sepsis incidence and mortality, 1990-2017: analysis for the Global Burden of Disease Study
10.1016/s0140-6736(19)32989-7 · 2020 · External reference
The challenging road of moving from association to causation for microbiome research in idiopathic pulmonary fibrosis
10.1164/rccm.201902-0318ed · 2019 · External reference
Applications of artificial neural networks in health care organizational decision-making: a scoping review
10.1371/journal.pone.0212356 · 2019 · External reference
P274 Cognitive function in idiopathic pulmonary fibrosis
10.1136/thoraxjnl-2016-209333.417 · 2016 · External reference
Developing prediction models for clinical use using logistic regression: an overview
10.21037/jtd.2019.01.25 · 2019 · External reference
The third international consensus definitions for sepsis and septic shock (Sepsis-3)
10.1001/jama.2016.0287 · 2016 · External reference
Emerging concepts in fibroblast biology and progressive pulmonary fibrosis
10.1055/a-2649-9359 · 2025 · External reference
The value of machine and deep learning in management of critically ill patients: an umbrella review
10.1016/j.ijmedinf.2025.106081 · 2025 · External reference
The incidence of acute exacerbation of idiopathic pulmonary fibrosis: a systematic review and meta-analysis
10.1038/s41598-024-71845-x · 2024 · External reference
Fibrotic lung disease inhibits immune responses to staphylococcal pneumonia via impaired neutrophil and macrophage function
10.1172/jci.insight.152690 · 2022 · External reference
diopathic pulmonary fibrosis in sepsis is a predictor of worse clinical outcomes and increase health care utilization cost. (SHM Converge)
2022 · External reference
Differences in clinical characteristics and outcomes between men and women with idiopathic pulmonary fibrosis: a multicenter retrospective cohort study
10.1016/j.chest.2020.02.009 · 2020 · External reference
Incidence and impact of extra-pulmonary organ failures on hospital mortality in acute exacerbation of idiopathic pulmonary fibrosis
10.1038/s41598-020-67598-y · 2020 · External reference
