Machine learning-based early prediction of sepsis using electronic health records: a systematic review
Background: Sepsis, a life-threatening infection-induced inflammatory condition, has
significant global health impacts. Timely detection is crucial for improving patient outcomes …
significant global health impacts. Timely detection is crucial for improving patient outcomes …
Artificial intelligence for clinical decision support for monitoring patients in cardiovascular ICUs: a systematic review
Background Artificial intelligence (AI) and machine learning (ML) models continue to evolve
the clinical decision support systems (CDSS). However, challenges arise when it comes to …
the clinical decision support systems (CDSS). However, challenges arise when it comes to …
[HTML][HTML] Feature selection and importance of predictors of non-communicable diseases medication adherence from machine learning research perspectives
W Kanyongo, AE Ezugwu - Informatics in Medicine Unlocked, 2023 - Elsevier
Medication nonadherence is a significant public health concern that leads to ineffective
treatment, which in turn engenders complications such as increased morbidity risks …
treatment, which in turn engenders complications such as increased morbidity risks …
Construction and validation of machine learning models for sepsis prediction in patients with acute pancreatitis
F Liu, J Yao, C Liu, S Shou - BMC surgery, 2023 - Springer
Background This study aimed to construct predictive models for the risk of sepsis in patients
with Acute pancreatitis (AP) using machine learning methods and compared optimal one …
with Acute pancreatitis (AP) using machine learning methods and compared optimal one …
Machine learning algorithms in sepsis
Sepsis remains a significant global health challenge due to its high mortality and morbidity,
compounded by the difficulty of early detection given its variable clinical manifestations. The …
compounded by the difficulty of early detection given its variable clinical manifestations. The …
Early prediction of sepsis using double fusion of deep features and handcrafted features
Y Duan, J Huo, M Chen, F Hou, G Yan, S Li, H Wang - Applied Intelligence, 2023 - Springer
Sepsis is a life-threatening medical condition that is characterized by the dysregulated
immune system response to infections, having both high morbidity and mortality rates. Early …
immune system response to infections, having both high morbidity and mortality rates. Early …
In-hospital mortality of sepsis differs depending on the origin of infection: an investigation of predisposing factors
Sepsis is a heterogeneous syndrome characterized by a variety of clinical features. Analysis
of large clinical datasets may serve to define groups of sepsis with different risks of adverse …
of large clinical datasets may serve to define groups of sepsis with different risks of adverse …
Predicting sepsis onset in ICU using machine learning models: a systematic review and meta-analysis
Z Yang, X Cui, Z Song - BMC infectious diseases, 2023 - Springer
Background Sepsis is a life-threatening condition caused by an abnormal response of the
body to infection and imposes a significant health and economic burden worldwide due to its …
body to infection and imposes a significant health and economic burden worldwide due to its …
Integrative single-cell RNA sequencing and metabolomics decipher the imbalanced lipid-metabolism in maladaptive immune responses during sepsis
H She, L Tan, Y Wang, Y Du, Y Zhou, J Zhang… - Frontiers in …, 2023 - frontiersin.org
Background To identify differentially expressed lipid metabolism-related genes (DE-LMRGs)
responsible for immune dysfunction in sepsis. Methods The lipid metabolism-related hub …
responsible for immune dysfunction in sepsis. Methods The lipid metabolism-related hub …
[HTML][HTML] Machine learning predicts the risk of hemorrhagic transformation of acute cerebral infarction and in-hospital death
X Li, C Xu, C Shang, Y Wang, J Xu, Q Zhou - Computer Methods and …, 2023 - Elsevier
Background The incidence of hemorrhagic transformation (HT) during thrombolysis after
acute cerebral infarction (ACI) is very high. We aimed to develop a model to predict the …
acute cerebral infarction (ACI) is very high. We aimed to develop a model to predict the …