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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7371836 | PMC |
| http://dx.doi.org/10.1186/s13010-020-00089-0 | DOI Listing |
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Integrating Interpretability in Machine Learning and Deep Neural Networks: A Novel Approach to Feature Importance and Outlier Detection in COVID-19 Symptomatology and Vaccine Efficacy.
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Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.
In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. Our method bridges the gap between interpretable ML models and powerful deep learning (DL) architectures, providing comprehensive insights into the key drivers behind model predictions, especially in detecting outliers within medical data. We applied this method to analyze COVID-19 pandemic data from 2020, yielding intriguing insights.
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World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
The world has gone through the COVID-19 pandemic and has now returned to normalcy. We reviewed the strategies and public health actions conducted in Hong Kong during the COVID-19 pandemic, and reflected on the lessons learned, which are potentially useful in the fight against antimicrobial resistance (AMR). We recommended extending wastewater surveillance for AMR, apart from SARS-CoV2.
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Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a member of the large coronavirus family with high infectivity and pathogenicity and is the primary pathogen causing the global pandemic of coronavirus disease 2019 (COVID-19). Phosphorylation is a major type of protein post-translational modification that plays an essential role in the process of SARS-CoV-2-host interactions. The precise identification of phosphorylation sites in host cells infected with SARS-CoV-2 will be of great importance to investigate potential antiviral responses and mechanisms and exploit novel targets for therapeutic development.
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Department of Clinical and Experimental Medicine, School and Operative Unit of Allergy and Clinical Immunology, University of Messina, 98125 Messina, Italy.
The SARS-CoV-2 pandemic has significantly impacted global health and has led the population and the scientific community to live in fear of a future pandemic. Based on viral infectious diseases, innate immunity cells such as mast cells and basophils play a fundamental role in the pathogenesis of viral diseases. Understanding these mechanisms could be essential to better study practical therapeutic approaches not only to COVID-19 but also to other viral infections widely spread worldwide, such as influenza A, HIV, and dengue.
View Article and Find Full Text PDFAutoML-Driven Insights into Patient Outcomes and Emergency Care During Romania's First Wave of COVID-19.
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Department of Dermatology, Venereology and Allergology, University Medical Center and Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany.
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