Last Posted: Apr 23, 2021
- Development and Validation of a Machine Learning Model to Estimate Bacterial Sepsis Among Immunocompromised Recipients of Stem Cell Transplant.
Lind Margaret L et al. JAMA network open 2021 4(4) e214514 - Physiological machine learning models for prediction of sepsis in hospitalized adults: An integrative review.
Kausch Sherry L et al. Intensive & critical care nursing 2021 103035 - Characterization of antimicrobial-resistant Gram-negative bacteria that cause neonatal sepsis in seven low- and middle-income countries.
Sands Kirsty et al. Nature microbiology 2021 3 (4) 512-523 - Prediction of Sepsis in COVID-19 Using Laboratory Indicators.
Tang Guoxing et al. Frontiers in cellular and infection microbiology 2021 10586054 - A Simulated Prospective Evaluation of a Deep Learning Model for Real-Time Prediction of Clinical Deterioration Among Ward Patients.
Shah Parth K et al. Critical care medicine 2021 - Early Detection of Sepsis With Machine Learning Techniques: A Brief Clinical Perspective.
Giacobbe Daniele Roberto et al. Frontiers in medicine 2021 8617486 - Feasibility of Embedding a Scalable, Virtually Enabled Biorepository in the Electronic Health Record for Precision Medicine.
DeMerle Kimberley M et al. JAMA network open 2021 4(2) e2037739 - Development and Validation of an Automated Algorithm to Detect Atrial Fibrillation Within Stored Intensive Care Unit Continuous Electrocardiographic Data: Observational Study.
Walkey Allan J et al. JMIR cardio 2021 Feb 5(1) e18840 - A Machine-Learning Approach for Dynamic Prediction of Sepsis-Induced Coagulopathy in Critically Ill Patients With Sepsis.
Zhao Qin-Yu et al. Frontiers in medicine 2020 7637434 - Prediction of Late-Onset Sepsis in Preterm Infants Using Monitoring Signals and Machine Learning.
Cabrera-Quiros Laura et al. Critical care explorations 2021 Jan 3(1) e0302
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Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.
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