[HTML][HTML] Artificial intelligence for COVID-19: a systematic review
L Wang, Y Zhang, D Wang, X Tong, T Liu… - Frontiers in …, 2021 - frontiersin.org
Background: Recently, Coronavirus Disease 2019 (COVID-19), caused by severe acute
respiratory syndrome virus 2 (SARS-CoV-2), has affected more than 200 countries and lead …
respiratory syndrome virus 2 (SARS-CoV-2), has affected more than 200 countries and lead …
[HTML][HTML] Artificial intelligence in clinical care amidst COVID-19 pandemic: a systematic review
The worldwide health crisis caused by the SARS-Cov-2 virus has resulted in more than 3
million deaths so far. Improving early screening, diagnosis and prognosis of the disease are …
million deaths so far. Improving early screening, diagnosis and prognosis of the disease are …
Latent class analysis reveals COVID-19–related acute respiratory distress syndrome subgroups with differential responses to corticosteroids
P Sinha, D Furfaro, MJ Cummings… - American journal of …, 2021 - atsjournals.org
Rationale: Two distinct subphenotypes have been identified in acute respiratory distress
syndrome (ARDS), but the presence of subgroups in ARDS associated with coronavirus …
syndrome (ARDS), but the presence of subgroups in ARDS associated with coronavirus …
Deep learning models for COVID-19 infected area segmentation in CT images
A Voulodimos, E Protopapadakis… - Proceedings of the 14th …, 2021 - dl.acm.org
Recent studies indicated that detecting radiographic patterns on CT chest scans can yield
high sensitivity and specificity for COVID-19 detection. In this work, we scrutinize the …
high sensitivity and specificity for COVID-19 detection. In this work, we scrutinize the …
Application of a data-driven XGBoost model for the prediction of COVID-19 in the USA: a time-series study
Z Fang, S Yang, C Lv, S An, W Wu - BMJ open, 2022 - bmjopen.bmj.com
Objective The COVID-19 outbreak was first reported in Wuhan, China, and has been
acknowledged as a pandemic due to its rapid spread worldwide. Predicting the trend of …
acknowledged as a pandemic due to its rapid spread worldwide. Predicting the trend of …
COVID-19 mortality prediction in the intensive care unit with deep learning based on longitudinal chest X-rays and clinical data
Objectives We aimed to develop deep learning models using longitudinal chest X-rays
(CXRs) and clinical data to predict in-hospital mortality of COVID-19 patients in the intensive …
(CXRs) and clinical data to predict in-hospital mortality of COVID-19 patients in the intensive …
The application of artificial intelligence and data integration in COVID-19 studies: a scoping review
Objective To summarize how artificial intelligence (AI) is being applied in COVID-19
research and determine whether these AI applications integrated heterogenous data from …
research and determine whether these AI applications integrated heterogenous data from …
Diagnosis and prognosis of COVID-19 employing analysis of patients' plasma and serum via LC-MS and machine learning
A de Fátima Cobre, M Surek, DP Stremel… - Computers in biology …, 2022 - Elsevier
Objective To implement and evaluate machine learning (ML) algorithms for the prediction of
COVID-19 diagnosis, severity, and fatality and to assess biomarkers potentially associated …
COVID-19 diagnosis, severity, and fatality and to assess biomarkers potentially associated …
Performance of prediction models for short-term outcome in COVID-19 patients in the emergency department: a retrospective study
PMEL van Dam, N Zelis, SMJ van Kuijk… - Annals of …, 2021 - Taylor & Francis
Abstract Introduction Coronavirus disease 2019 (COVID-19) has a high burden on the
healthcare system. Prediction models may assist in triaging patients. We aimed to assess …
healthcare system. Prediction models may assist in triaging patients. We aimed to assess …
Early and fair COVID-19 outcome risk assessment using robust feature selection
Personalized medicine plays an important role in treatment optimization for COVID-19
patient management. Early treatment in patients at high risk of severe complications is vital …
patient management. Early treatment in patients at high risk of severe complications is vital …