1
Predicting sepsis with a recurrent neural network using the MIMIC III database
2
A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis.
3
A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice.
5
Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs
6
MySurgeryRisk: Development and Validation of a Machine-learning Risk Algorithm for Major Complications and Death After Surgery
7
A minimal set of physiomarkers in continuous high frequency data streams predict adult sepsis onset earlier
8
Improving Prediction Performance Using Hierarchical Analysis of Real-Time Data: A Sepsis Case Study
9
Development and Evaluation of a Machine Learning Model for the Early Identification of Patients at Risk for Sepsis
10
The efficacy and effectiveness of machine learning for weaning in mechanically ventilated patients at the intensive care unit: a systematic review
11
Early PREdiction of sepsis using leukocyte surface biomarkers: the ExPRES-sepsis cohort study
12
Prediction of Sepsis and In-Hospital Mortality Using Electronic Health Records
13
Comparing the validity of different ICD coding abstraction strategies for sepsis case identification in German claims data
14
UDAY: A comprehensive diabetes and hypertension prevention and management program in India
15
Circulating biomarkers may be unable to detect infection at the early phase of sepsis in ICU patients: the CAPTAIN prospective multicenter cohort study
16
Arguing for Adaptive Clinical Trials in Sepsis
17
Recent Temporal Pattern Mining for Septic Shock Early Prediction
18
Early Diagnosis and Prediction of Sepsis Shock by Combining Static and Dynamic Information Using Convolutional-LSTM
19
Predictive Models of Sepsis in Adult ICU Patients
20
Artificial intelligence in healthcare
21
Big Data and Machine Learning in Health Care.
22
Unexplained mortality differences between septic shock trials: a systematic analysis of population characteristics and control-group mortality rates
23
Epidemiological trends of sepsis in the twenty-first century (2000–2013): an analysis of incidence, mortality, and associated costs in Spain
24
Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies: The PRISMA-DTA Statement
25
Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU
26
A Comparison of the Quick‐SOFA and Systemic Inflammatory Response Syndrome Criteria for the Diagnosis of Sepsis and Prediction of Mortality: A Systematic Review and Meta‐Analysis
27
An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU
28
Multiscale network representation of physiological time series for early prediction of sepsis
29
Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial
30
Early sepsis detection in critical care patients using multiscale blood pressure and heart rate dynamics.
31
Incidence and Trends of Sepsis in US Hospitals Using Clinical vs Claims Data, 2009-2014
32
Impact of an electronic sepsis initiative on antibiotic use and health care facility–onset Clostridium difficile infection rates
33
Reducing patient mortality, length of stay and readmissions through machine learning-based sepsis prediction in the emergency department, intensive care unit and hospital floor units
34
Learning representations for the early detection of sepsis with deep neural networks
35
The Timing of Early Antibiotics and Hospital Mortality in Sepsis
36
Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier
37
Time to Treatment and Mortality during Mandated Emergency Care for Sepsis
38
Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning
39
Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock: 2016
40
Use of explicit ICD9-CM codes to identify adult severe sepsis: impacts on epidemiological estimates
41
Using a Semi-Automated Modeling Environment to Construct a Bayesian, Sepsis Diagnostic System
42
Prediction of Sepsis in the Intensive Care Unit With Minimal Electronic Health Record Data: A Machine Learning Approach
43
Signatures of Subacute Potentially Catastrophic Illness in the ICU: Model Development and Validation*
44
Prospective evaluation of an automated method to identify patients with severe sepsis or septic shock in the emergency department
45
Assessment of clinical criteria for sepsis-was the cart put before the horse?
46
A computational approach to early sepsis detection
47
Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications
48
High-performance detection and early prediction of septic shock for alcohol-use disorder patients
49
The Clinical Challenge of Sepsis Identification and Monitoring
50
Assessment of Clinical Criteria for Sepsis: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).
51
Developing a New Definition and Assessing New Clinical Criteria for Septic Shock: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).
52
Assessment of Global Incidence and Mortality of Hospital-treated Sepsis. Current Estimates and Limitations.
53
Predictive role of high sensitivity troponin T within four hours from presentation of acute coronary syndrome in elderly patients
54
The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3)
55
A targeted real-time early warning score (TREWScore) for septic shock
56
Diagnostic accuracy and effectiveness of automated electronic sepsis alert systems: A systematic review.
57
Predictive models for severe sepsis in adult ICU patients
58
Diagnostic accuracy of a screening electronic alert tool for severe sepsis and septic shock in the emergency department
59
Circulating MicroRNAs as a Novel Class of Diagnostic Biomarkers in Gastrointestinal Tumors Detection: A Meta-Analysis Based on 42 Articles
60
Empiric Antibiotic Treatment Reduces Mortality in Severe Sepsis and Septic Shock From the First Hour: Results From a Guideline-Based Performance Improvement Program*
61
Automated electronic medical record sepsis detection in the emergency department
62
NEWSDIG: The National Early Warning Score Development and Implementation Group.
63
Randomized trial of automated, electronic monitoring to facilitate early detection of sepsis in the intensive care unit*
64
Prospective trial of real-time electronic surveillance to expedite early care of severe sepsis.
65
Learning from Imbalanced Data
66
Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock*
68
Learning From Imbalanced Data
69
Supervised learning—scikit-learn 0.21.2 documentation
70
Critical Appraisal Tools|Joanna Briggs Institute
71
R: A language and environment for statistical computing.
72
Early Detection of Sepsis in the Emergency Department using Dynamic Bayesian Networks
73
Early prediction of septic shock in hospitalized patients.
74
Grading quality of evidence and strength of recommendations
