Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
Abstract Machine learning methods offer great promise for fast and accurate detection and
prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest …
prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest …
Diagnosing COVID-19 using artificial intelligence: A comprehensive review
Abstract In early March 2020, the World Health Organization (WHO) proclaimed the novel
COVID-19 as a global pandemic. The coronavirus went on to be a life-threatening infection …
COVID-19 as a global pandemic. The coronavirus went on to be a life-threatening infection …
A novel extended approach under hesitant fuzzy sets to design a framework for assessing the key challenges of digital health interventions adoption during the COVID …
Abstract In recent years, Digital Technologies (DTs) are becoming an inseparable part of
human lives. Thus, many scholars have conducted research to develop new tools and …
human lives. Thus, many scholars have conducted research to develop new tools and …
A multipurpose machine learning approach to predict COVID-19 negative prognosis in São Paulo, Brazil
The new coronavirus disease (COVID-19) is a challenge for clinical decision-making and
the effective allocation of healthcare resources. An accurate prognostic assessment is …
the effective allocation of healthcare resources. An accurate prognostic assessment is …
[PDF][PDF] Machine learning with multimodal data for COVID-19
In response to the unprecedented global healthcare crisis of the COVID-19 pandemic, the
scientific community has joined forces to tackle the challenges and prepare for future …
scientific community has joined forces to tackle the challenges and prepare for future …
[HTML][HTML] Chest CT imaging features and severity scores as biomarkers for prognostic prediction in patients with COVID-19
S Zhou, C Chen, Y Hu, W Lv, T Ai… - Annals of translational …, 2020 - ncbi.nlm.nih.gov
Background Coronavirus disease 2019 (COVID-19) has become a pandemic. Few studies
have explored the role of chest computed tomography (CT) features and severity scores for …
have explored the role of chest computed tomography (CT) features and severity scores for …
Performance improvement of decision tree: A robust classifier using tabu search algorithm
Classification and regression are the major applications of machine learning algorithms
which are widely used to solve problems in numerous domains of engineering and …
which are widely used to solve problems in numerous domains of engineering and …
[HTML][HTML] Updates on laboratory investigations in coronavirus disease 2019 (COVID-19)
Abstract The coronavirus disease 2019 (COVID-19) pandemic is still spreading worldwide,
affecting several million people. Unlike the previous two coronavirus outbreaks, COVID-19 …
affecting several million people. Unlike the previous two coronavirus outbreaks, COVID-19 …
Machine learning-based CT radiomics model distinguishes COVID-19 from non-COVID-19 pneumonia
Background To develop a machine learning-based CT radiomics model is critical for the
accurate diagnosis of the rapid spreading coronavirus disease 2019 (COVID-19). Methods …
accurate diagnosis of the rapid spreading coronavirus disease 2019 (COVID-19). Methods …
One-on-one comparison between qCSI and NEWS scores for mortality risk assessment in patients with COVID-19
Objective To compare the predictive value of the quick COVID-19 Severity Index (qCSI) and
the National Early Warning Score (NEWS) for 90-day mortality amongst COVID-19 patients …
the National Early Warning Score (NEWS) for 90-day mortality amongst COVID-19 patients …