Related references
Note: Only part of the references are listed.Prevalence of dementia and its impact on mortality in patients with coronavirus disease 2019: A systematic review and meta-analysis
Julius July et al.
GERIATRICS & GERONTOLOGY INTERNATIONAL (2021)
The prognostic value of comorbidity for the severity of COVID-19: A systematic review and meta-analysis study
Mobina Fathi et al.
PLOS ONE (2021)
Association of smoking history with severe and critical outcomes in COVID-19 patients: A systemic review and meta-analysis
Huimei Zhang et al.
EUROPEAN JOURNAL OF INTEGRATIVE MEDICINE (2021)
Classification and Categorization of COVID-19 Outbreak in Pakistan
Amber Ayoub et al.
CMC-COMPUTERS MATERIALS & CONTINUA (2021)
Scarce-Resource Allocation and Patient Triage During the COVID-19 Pandemic JACC Review Topic of the Week
James N. Kirkpatrick et al.
JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY (2020)
The multifaceted long-term effects of the COVID-19 pandemic on urology
Alessandro Morlacco et al.
NATURE REVIEWS UROLOGY (2020)
Hyperglycemia at Hospital Admission Is Associated With Severity of the Prognosis in Patients Hospitalized for COVID-19: The Pisa COVID-19 Study
Alberto Coppelli et al.
DIABETES CARE (2020)
Artificial Intelligence in the Fight Against COVID-19: Scoping Review
Alaa Abd-Alrazaq et al.
JOURNAL OF MEDICAL INTERNET RESEARCH (2020)
Bayesian inference of COVID-19 spreading rates in South Africa
Rendani Mbuvha et al.
PLOS ONE (2020)
Underlying respiratory diseases, specifically COPD, and smoking are associated with severe COVID-19 outcomes: A systematic review and meta-analysis
Diana C. Sanchez-Ramirez et al.
RESPIRATORY MEDICINE (2020)
Which COVID policies are most effective? A Bayesian analysis of COVID-19 by jurisdiction
Phebo D. Wibbens et al.
PLOS ONE (2020)
Male sex identified by global COVID-19 meta-analysis as a risk factor for death and ITU admission
Hannah Peckham et al.
NATURE COMMUNICATIONS (2020)
When causal inference meets deep learning
Yunan Luo et al.
NATURE MACHINE INTELLIGENCE (2020)
The Association of Cerebrovascular Disease with Adverse Outcomes in COVID-19 Patients: A Meta-Analysis Based on Adjusted Effect Estimates
Jie Xu et al.
JOURNAL OF STROKE & CEREBROVASCULAR DISEASES (2020)
Acute complications and mortality in hospitalized patients with coronavirus disease 2019: a systematic review and meta-analysis
Nicola Potere et al.
CRITICAL CARE (2020)
Bayesian network analysis of Covid-19 data reveals higher infection prevalence rates and lower fatality rates than widely reported
Martin Neil et al.
JOURNAL OF RISK RESEARCH (2020)
COVID-19 pandemic management at the Emergency Department: the changing scenario at the University Hospital of Pisa
Greta Barbieri et al.
EMERGENCY CARE JOURNAL (2020)
Who learns better Bayesian network structures: Accuracy and speed of structure learning algorithms
Marco Scutari et al.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING (2019)
Learning the Structure of Bayesian Networks: A Quantitative Assessment of the Effect of Different Algorithmic Schemes
Stefano Beretta et al.
COMPLEXITY (2018)
Relating oxygen partial pressure, saturation and content: the haemoglobin-oxygen dissociation curve
Julie-Ann Collins et al.
BREATHE (2015)
Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission
Rich Caruana et al.
KDD'15: PROCEEDINGS OF THE 21ST ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING (2015)
Learning Bayesian networks for clinical time series analysis
Maarten van der Heijden et al.
JOURNAL OF BIOMEDICAL INFORMATICS (2014)
Causal Structure Learning and Inference: A Selective Review
Markus Kalisch et al.
QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT (2014)
Efficient identification of independence networks using mutual information
Davide Bacciu et al.
COMPUTATIONAL STATISTICS (2013)
Incorporating expert knowledge when learning Bayesian network structure: A medical case study
M. Julia Flores et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2011)
Learning genetic epistasis using Bayesian network scoring criteria
Xia Jiang et al.
BMC BIOINFORMATICS (2011)
Learning Bayesian networks: approaches and issues
Ronan Daly et al.
KNOWLEDGE ENGINEERING REVIEW (2011)
Advantages and challenges of Bayesian networks in environmental modelling
Laura Uusitalo
ECOLOGICAL MODELLING (2007)
Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement
BG Marcot et al.
FOREST ECOLOGY AND MANAGEMENT (2001)
Medical progress - The acute respiratory distress syndrome.
LB Ware et al.
NEW ENGLAND JOURNAL OF MEDICINE (2000)