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References from Artificial intelligence in clinical care amidst COVID-19 pandemic: A systematic review. Local targets link to admitted publications; unresolved targets remain external evidence.
10.1056/nejmoa2001017
10.1056/nejmoa2001017 · External reference
Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy
10.1148/radiol.2020200905 · 2020 · External reference
Rapid triage for COVID-19 using routine clinical data for patients attending hospital: development and prospective validation of an artificial intelligence screening test
10.1016/s2589-7500(20)30274-0 · 2020 · External reference
10.1093/clinchem/hvaa200
10.1093/clinchem/hvaa200 · External reference
“Early Detection of Coronavirus Cases Using Chest X-ray Images
2020 · External reference
10.1101/2020.05.10.20096073
10.1101/2020.05.10.20096073 · External reference
10.1148/radiol.2020202944
10.1148/radiol.2020202944 · External reference
10.1101/2020.04.04.20052092
10.1101/2020.04.04.20052092 · External reference
10.1007/s42979-020-00216-w
10.1007/s42979-020-00216-w · External reference
A model based on CT radiomic features for predicting RT-PCR becoming negative in coronavirus disease 2019 (COVID-19) patients
2020 · External reference
Analysis of clinical features and imaging signs of COVID-19 with the assistance of artificial intelligence
2020 · External reference
The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration
10.1371/journal.pmed.1000100 · 2009 · External reference
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10.1016/s0003-4975(01)02870-3
10.1016/s0003-4975(01)02870-3 · External reference
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Individual-Level Fatality Prediction of COVID-19 Patients Using AI Methods
2020 · External reference
Predictive Models of Mortality for Hospitalized Patients With COVID-19: Retrospective Cohort Study
10.2196/21788 · 2020 · External reference
PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies
10.7326/m18-1376 · 2019 · External reference
10.1109/iscv49265.2020.9204282
10.1109/iscv49265.2020.9204282 · External reference
10.1016/j.media.2020.101794
10.1016/j.media.2020.101794 · External reference
10.1371/journal.pone.0235187
10.1371/journal.pone.0235187 · External reference
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10.1109/icosec49089.2020.9215257
10.1109/icosec49089.2020.9215257 · External reference
Experiments of Federated Learning for COVID-19 Chest X-ray Images
2020 · External reference
10.1016/j.compbiomed.2020.103869
10.1016/j.compbiomed.2020.103869 · External reference
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COVID-19 patient health prediction using boosted random forest algorithm
2020 · External reference
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10.2196/19569
10.2196/19569 · External reference
10.1109/isiea49364.2020.9188133
10.1109/isiea49364.2020.9188133 · External reference
Coronavirus (COVID-19) Classification using CT Images by Machine Learning Methods
2020 · External reference
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A modified deep convolutional neural network for detecting COVID-19 and pneumonia from chest X-ray images based on the concatenation of Xception and ResNet50V2
10.1016/j.imu.2020.100360 · 2020 · External reference
10.1016/j.asoc.2020.106742
10.1016/j.asoc.2020.106742 · External reference
10.1016/j.compbiomed.2020.103792
10.1016/j.compbiomed.2020.103792 · External reference
10.7759/cureus.9448
10.7759/cureus.9448 · External reference
Using Artificial Intelligence for COVID-19 Chest X-ray Diagnosis
2020 · External reference
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“CVDNet: A novel deep learning architecture for detection of coronavirus (Covid-19) from chest x-ray images”, Chaos
10.1016/j.chaos.2020.110245 · 2020 · External reference
10.1016/s0140-6736(20)30183-5
10.1016/s0140-6736(20)30183-5 · External reference
10.1101/2020.05.06.20092874
10.1101/2020.05.06.20092874 · External reference
10.1101/2020.03.20.20037325
10.1101/2020.03.20.20037325 · External reference
CT quantification of pneumonia lesions in early days predicts progression to severe illness in a cohort of COVID-19 patients
10.7150/thno.45985 · 2020 · External reference
10.1101/2020.04.17.20069187
10.1101/2020.04.17.20069187 · External reference
10.1109/icengtechnol.2017.8308186
10.1109/icengtechnol.2017.8308186 · External reference
10.1007/0-387-25465-x_9
10.1007/0-387-25465-x_9 · 2005 · External reference
10.7554/elife.60519
10.7554/elife.60519 · External reference
Measuring the Quality of Explanations: The System Causability Scale (SCS): Comparing Human and Machine Explanations
10.1007/s13218-020-00636-z · 2020 · External reference
Federated Learning of Electronic Health Records to Improve Mortality Prediction in Hospitalized Patients With COVID-19: Machine Learning Approach
10.2196/24207 · 2021 · External reference
Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data
10.1038/s41598-020-69250-1 · 2020 · External reference
Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker
10.1136/heartjnl-2011-301246 · 2012 · External reference
10.2307/2965703
10.2307/2965703 · External reference
10.1136/bmj.i3140
10.1136/bmj.i3140 · External reference
Deep learning-based multi-view fusion model for screening 2019 novel coronavirus pneumonia: A multicentre study
10.1016/j.ejrad.2020.109041 · 2020 · External reference
Deep learning-based triage and analysis of lesion burden for COVID-19: a retrospective study with external validation
10.1016/s2589-7500(20)30199-0 · 2020 · External reference
10.1101/2020.06.03.20120881
10.1101/2020.06.03.20120881 · External reference
10.1101/2020.04.10.20061036
10.1101/2020.04.10.20061036 · External reference
A Novel Triage Tool of Artificial Intelligence Assisted Diagnosis Aid System for Suspected COVID-19 Pneumonia in Fever Clinics
2020 · External reference
10.1101/2020.04.02.20051136
10.1101/2020.04.02.20051136 · External reference
Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population
10.1016/j.intimp.2020.106705 · 2020 · External reference
Artificial Intelligence Application in COVID-19 Diagnosis and Prediction
2020 · External reference
10.1101/2020.09.03.20184226
10.1101/2020.09.03.20184226 · External reference
10.1515/cclm-2020-1294
10.1515/cclm-2020-1294 · External reference
Artificial intelligence–enabled rapid diagnosis of patients with COVID-19
10.1038/s41591-020-0931-3 · 2020 · External reference
Joint prediction and time estimation of COVID-19 developing severe symptoms using chest CT scan
10.1016/j.media.2020.101824 · 2021 · External reference
10.1101/2020.02.29.20029603
10.1101/2020.02.29.20029603 · External reference
Development and Validation of a Deep Learning-Based Model Using Computed Tomography Imaging for Predicting Disease Severity of Coronavirus Disease 2019
2020 · External reference
10.1007/s11547-020-01293-w
10.1007/s11547-020-01293-w · External reference
10.1101/2020.03.30.20047308
10.1101/2020.03.30.20047308 · External reference
10.1038/s41467-020-18684-2
10.1038/s41467-020-18684-2 · External reference
Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound
10.1109/tmi.2020.2994459 · 2020 · External reference
10.1101/2020.03.24.20043117
10.1101/2020.03.24.20043117 · External reference
Prediction of COVID-19 Using Genetic Deep Learning Convolutional Neural Network (GDCNN)
10.1109/access.2020.3025164 · 2020 · External reference
Artificial Intelligence Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Origin at Chest CT
10.1148/radiol.2020201491 · 2020 · External reference
“Artificial intelligence applied on chest X-ray can aid in the diagnosis of COVID-19 infection: a first experience from Lombardy
2020 · External reference
Unresolved reference
2020 · External reference
Using Machine Learning to Predict ICU Transfer in Hospitalized COVID-19 Patients
10.3390/jcm9061668 · 2020 · External reference
An Easy-to-Use Machine Learning Model to Predict the Prognosis of Patients With COVID-19: Retrospective Cohort Study
10.2196/24225 · 2020 · External reference
COVID-19 mortality risk assessment: An international multi-center study
10.1371/journal.pone.0243262 · 2020 · External reference
10.1038/s41598-021-81844-x
10.1038/s41598-021-81844-x · External reference
Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial
10.1016/j.compbiomed.2020.103949 · 2020 · External reference
CT Quantification and Machine-learning Models for Assessment of Disease Severity and Prognosis of COVID-19 Patients
10.1016/j.acra.2020.09.004 · 2020 · External reference
A prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings
2020 · External reference
Development and validation of prognosis model of mortality risk in patients with COVID-19
2020 · External reference
Clinical Characteristics and Prognostic Factors for ICU Admission of Patients with COVID-19 Using Machine Learning and Natural Language Processing
10.2139/ssrn.3582866 · 2020 · External reference
10.1183/13993003.01104-2020
10.1183/13993003.01104-2020 · External reference
10.32604/cmc.2020.010691
10.32604/cmc.2020.010691 · External reference
Early triage of critically ill COVID-19 patients using deep learning
10.1038/s41467-020-17280-8 · 2020 · External reference
10.1093/cid/ciaa443
10.1093/cid/ciaa443 · External reference
10.2196/20259
10.2196/20259 · External reference
10.1038/s41598-020-76282-0
10.1038/s41598-020-76282-0 · External reference
10.21203/rs.3.rs-104621/v1
10.21203/rs.3.rs-104621/v1 · External reference
Automatic distinction between COVID-19 and common pneumonia using multi-scale convolutional neural network on chest CT scans
10.1016/j.chaos.2020.110153 · 2020 · External reference
10.5220/0010293605650570
10.5220/0010293605650570 · External reference
10.1038/s41467-020-18685-1
10.1038/s41467-020-18685-1 · External reference
Efficient and Effective Training of COVID-19 Classification Networks with Self-Supervised Dual-Track Learning to Rank
10.1109/jbhi.2020.3018181 · 2020 · External reference
Adaptive Feature Selection Guided Deep Forest for COVID-19 Classification with Chest CT
10.1109/jbhi.2020.3019505 · 2020 · External reference
10.1038/s41598-020-76550-z
10.1038/s41598-020-76550-z · External reference
10.1016/j.cell.2020.04.045
10.1016/j.cell.2020.04.045 · External reference
10.1016/j.cell.2020.08.029
10.1016/j.cell.2020.08.029 · External reference
10.1016/s2589-7500(20)30217-x
10.1016/s2589-7500(20)30217-x · External reference
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10.1101/2020.08.23.20179838
10.1101/2020.08.23.20179838 · External reference
Development and Prospective Validation of a Deep Learning Algorithm for Predicting Need for Mechanical Ventilation
2020 · External reference
10.1101/2020.11.04.20225904
10.1101/2020.11.04.20225904 · External reference
10.1101/2020.08.19.20177477
10.1101/2020.08.19.20177477 · External reference
10.1109/access.2020.3034032
10.1109/access.2020.3034032 · External reference
10.1101/2020.02.27.20028027
10.1101/2020.02.27.20028027 · External reference
10.2196/21439
10.2196/21439 · External reference
Machine-Learning Approaches in COVID-19 Survival Analysis and Discharge-Time Likelihood Prediction Using Clinical Data
10.1016/j.patter.2020.100074 · 2020 · External reference
10.1002/emp2.12205
10.1002/emp2.12205 · External reference
Machine Learning to Predict Mortality and Critical Events in COVID-19 Positive New York City Patients: A Cohort Study (Preprint)
10.2196/24018 · 2020 · External reference
10.1016/j.ijmedinf.2020.104258
10.1016/j.ijmedinf.2020.104258 · External reference
10.1016/j.jcv.2020.104431
10.1016/j.jcv.2020.104431 · External reference
10.1038/s41746-020-00343-x
10.1038/s41746-020-00343-x · External reference
Utilization of machine-learning models to accurately predict the risk for critical COVID-19
10.1007/s11739-020-02475-0 · 2020 · External reference
10.1101/2020.10.15.20213462
10.1101/2020.10.15.20213462 · External reference
Mortality prediction model for the triage of COVID-19, pneumonia, and mechanically ventilated ICU patients: A retrospective study
10.1016/j.amsu.2020.09.044 · 2020 · External reference
10.1109/tnnls.2020.3027314
10.1109/tnnls.2020.3027314 · External reference
10.36227/techrxiv.12942299.v1
10.36227/techrxiv.12942299.v1 · External reference
