Review on the evaluation and development of artificial intelligence for COVID-19 containment

MM Hasan, MU Islam, MJ Sadeq, WK Fung, J Uddin - Sensors, 2023 - mdpi.com
Artificial intelligence has significantly enhanced the research paradigm and spectrum with a
substantiated promise of continuous applicability in the real world domain. Artificial …

Methodology-centered review of molecular modeling, simulation, and prediction of SARS-CoV-2

K Gao, R Wang, J Chen, L Cheng, J Frishcosy… - Chemical …, 2022 - ACS Publications
Despite tremendous efforts in the past two years, our understanding of severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2), virus–host interactions, immune …

Comparing machine learning algorithms for predicting COVID-19 mortality

K Moulaei, M Shanbehzadeh… - BMC medical informatics …, 2022 - Springer
Background The coronavirus disease (COVID-19) hospitalized patients are always at risk of
death. Machine learning (ML) algorithms can be used as a potential solution for predicting …

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 …

[HTML][HTML] Machine learning decision tree algorithm role for predicting mortality in critically ill adult COVID-19 patients admitted to the ICU

A Elhazmi, A Al-Omari, H Sallam, HN Mufti… - Journal of infection and …, 2022 - Elsevier
Abstract Background Coronavirus disease-19 (COVID-19) is caused by the severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2) and is currently a major cause of …

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 …

Prediction of diagnosis and prognosis of COVID-19 disease by blood gas parameters using decision trees machine learning model: a retrospective observational …

MT Huyut, H Üstündağ - Medical gas research, 2022 - journals.lww.com
Abstract The coronavirus disease 2019 (COVID-19) epidemic went down in history as a
pandemic caused by corona-viruses that emerged in 2019 and spread rapidly around the …

[HTML][HTML] Artificial intelligence in clinical care amidst COVID-19 pandemic: a systematic review

ES Adamidi, K Mitsis, KS Nikita - Computational and structural …, 2021 - Elsevier
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 …

Artificial intelligence: machine learning for chemical sciences

A Karthikeyan, UD Priyakumar - Journal of Chemical Sciences, 2022 - Springer
Research in molecular sciences witnessed the rise and fall of Artificial Intelligence
(AI)/Machine Learning (ML) methods, especially artificial neural networks, few decades ago …

Predictive models for COVID-19 detection using routine blood tests and machine learning

YV Kistenev, DA Vrazhnov, EE Shnaider, H Zuhayri - Heliyon, 2022 - cell.com
The problem of accurate, fast, and inexpensive COVID-19 tests has been urgent till now.
Standard COVID-19 tests need high-cost reagents and specialized laboratories with high …