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Sepsis

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A dosing strategy model of deep deterministic policy gradient algorithm for sepsis patients.

BMC medical informatics and decision making
BACKGROUND: A growing body of research suggests that the use of computerized decision support systems can better guide disease treatment and reduce the use of social and medical resources. Artificial intelligence (AI) technology is increasingly being...

Exploring a global interpretation mechanism for deep learning networks when predicting sepsis.

Scientific reports
The purpose of this study is to identify additional clinical features for sepsis detection through the use of a novel mechanism for interpreting black-box machine learning models trained and to provide a suitable evaluation for the mechanism. We use ...

FedSepsis: A Federated Multi-Modal Deep Learning-Based Internet of Medical Things Application for Early Detection of Sepsis from Electronic Health Records Using Raspberry Pi and Jetson Nano Devices.

Sensors (Basel, Switzerland)
The concept of the Internet of Medical Things brings a promising option to utilize various electronic health records stored in different medical devices and servers to create practical but secure clinical decision support systems. To achieve such a s...

OnAI-Comp: An Online AI Experts Competing Framework for Early Sepsis Detection.

IEEE/ACM transactions on computational biology and bioinformatics
Sepsis is a major public concern due to its high mortality, morbidity, and financial cost. There are many existing works of early sepsis prediction using different machine learning models to mitigate the outcomes brought by sepsis. In the practical s...

Identification of two robust subclasses of sepsis with both prognostic and therapeutic values based on machine learning analysis.

Frontiers in immunology
BACKGROUND: Sepsis is a heterogeneous syndrome with high morbidity and mortality. Optimal and effective classifications are in urgent need and to be developed.

Diagnostic performance of machine learning models using cell population data for the detection of sepsis: a comparative study.

Clinical chemistry and laboratory medicine
OBJECTIVES: To compare the artificial intelligence algorithms as powerful machine learning methods for evaluating patients with suspected sepsis using data from routinely available blood tests performed on arrival at the hospital. Results were compar...

Predicting risk of sepsis, comparison between machine learning methods: a case study of a Virginia hospital.

European journal of medical research
Sepsis is an inflammation caused by the body's systemic response to an infection. The infection could be a result of many diseases, such as pneumonia, urinary tract infection, and other illnesses. Some of its symptoms are fever, tachycardia, tachypne...

Dynamic Sepsis Prediction for Intensive Care Unit Patients Using XGBoost-Based Model With Novel Time-Dependent Features.

IEEE journal of biomedical and health informatics
Sepsis is a systemic inflammatory response caused by pathogens such as bacteria. Because its pathogenesis is not clear, the clinical manifestations of patients vary greatly, and the alarming incidence and mortality pose a great threat to patients and...