Machine learning for clinical decision support in infectious diseases: a narrative review of current applications
Background Machine learning (ML) is a growing field in medicine. This narrative review
describes the current body of literature on ML for clinical decision support in infectious …
describes the current body of literature on ML for clinical decision support in infectious …
Emerging technologies for molecular diagnosis of sepsis
Rapid and accurate profiling of infection-causing pathogens remains a significant challenge
in modern health care. Despite advances in molecular diagnostic techniques, blood culture …
in modern health care. Despite advances in molecular diagnostic techniques, blood culture …
A survey on medical explainable AI (XAI): recent progress, explainability approach, human interaction and scoring system
The emerging field of eXplainable AI (XAI) in the medical domain is considered to be of
utmost importance. Meanwhile, incorporating explanations in the medical domain with …
utmost importance. Meanwhile, incorporating explanations in the medical domain with …
The potential of artificial intelligence to improve patient safety: a sco** review
Artificial intelligence (AI) represents a valuable tool that could be used to improve the safety
of care. Major adverse events in healthcare include: healthcare-associated infections …
of care. Major adverse events in healthcare include: healthcare-associated infections …
[HTML][HTML] Clinical applications of artificial intelligence in sepsis: a narrative review
Many studies have been published on a variety of clinical applications of artificial
intelligence (AI) for sepsis, while there is no overview of the literature. The aim of this review …
intelligence (AI) for sepsis, while there is no overview of the literature. The aim of this review …
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 …
Micro-and nanosensors for detecting blood pathogens and biomarkers at different points of sepsis care
A Alba-Patiño, A Vaquer, E Barón, SM Russell… - Microchimica Acta, 2022 - Springer
Severe infections can cause a dysregulated response leading to organ dysfunction known
as sepsis. Sepsis can be lethal if not identified and treated right away. This requires …
as sepsis. Sepsis can be lethal if not identified and treated right away. This requires …
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 …
Evaluating machine learning models for sepsis prediction: A systematic review of methodologies
HF Deng, MW Sun, Y Wang, J Zeng, T Yuan, T Li… - Iscience, 2022 - cell.com
Studies for sepsis prediction using machine learning are develo** rapidly in medical
science recently. In this review, we propose a set of new evaluation criteria and reporting …
science recently. In this review, we propose a set of new evaluation criteria and reporting …
Early detection of sepsis with machine learning techniques: a brief clinical perspective
Sepsis is a major cause of death worldwide. Over the past years, prediction of clinically
relevant events through machine learning models has gained particular attention. In the …
relevant events through machine learning models has gained particular attention. In the …