AIMC Topic: COVID-19

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The value of federated learning during and post-COVID-19.

International journal for quality in health care : journal of the International Society for Quality in Health Care
Federated learning (FL) as a distributed machine learning (ML) technique has lately attracted increasing attention of healthcare stakeholders as FL is perceived as a promising decentralized approach to address data privacy and security concerns. The ...

COVID-19 mortality rate prediction for India using statistical neural networks and gaussian process regression model.

African health sciences
The primary purpose of this research is to identify the best COVID-19 mortality model for India using regression models and is to estimate the future COVID-19 mortality rate for India. Specifically, Statistical Neural Networks (Radial Basis Function ...

Use of Telepresence Robots in Glaucoma Patient Education.

Journal of glaucoma
PRCIS: Telepresence robots (TR) present the versatility to effectively provide remote educational sessions for patients affected by glaucoma to improve disease knowledge. Given COVID-19's effect on clinical practice, TR can maintain social distancing...

FLANNEL (Focal Loss bAsed Neural Network EnsembLe) for COVID-19 detection.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The study sought to test the possibility of differentiating chest x-ray images of coronavirus disease 2019 (COVID-19) against other pneumonia and healthy patients using deep neural networks.

Using machine learning to estimate the effect of racial segregation on COVID-19 mortality in the United States.

Proceedings of the National Academy of Sciences of the United States of America
This study examines the role that racial residential segregation has played in shaping the spread of COVID-19 in the United States as of September 30, 2020. The analysis focuses on the effects of racial residential segregation on mortality and infect...

Potential limitations in COVID-19 machine learning due to data source variability: A case study in the nCov2019 dataset.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The lack of representative coronavirus disease 2019 (COVID-19) data is a bottleneck for reliable and generalizable machine learning. Data sharing is insufficient without data quality, in which source variability plays an important role. We...

Exploring the Influential Factors of Consumers' Willingness Toward Using COVID-19 Related Chatbots: An Empirical Study.

Medical archives (Sarajevo, Bosnia and Herzegovina)
BACKGROUND: Consumers' willingness to use health chatbots can eventually determine if the adoption of health chatbots will succeed in delivering healthcare services for combating COVID-19. However, little research to date has empirically explored inf...

Using machine learning to investigate the public's emotional responses to work from home during the COVID-19 pandemic.

The Journal of applied psychology
According to event system theory (EST; Morgeson et al., Academy of Management Review, 40, 2015, 515-537), the coronavirus disease 2019 (COVID-19) pandemic and resultant stay-at-home orders are novel, critical, and disruptive events at the environment...

Artificial intelligence enabled preliminary diagnosis for COVID-19 from voice cues and questionnaires.

The Journal of the Acoustical Society of America
The COVID-19 outbreak was announced as a global pandemic by the World Health Organization in March 2020 and has affected a growing number of people in the past few months. In this context, advanced artificial intelligence techniques are brought to th...