-
A Survey on Applications of Artificial Intelligence in Fighting Against COVID-19
The COVID-19 pandemic caused by the SARS-CoV-2 virus has spread rapidly ...
read it
-
Artificial Intelligence-based Clinical Decision Support for COVID-19 – Where Art Thou?
The COVID-19 crisis has brought about new clinical questions, new workfl...
read it
-
Tracking Results and Utilization of Artificial Intelligence (tru-AI) in Radiology: Early-Stage COVID-19 Pandemic Observations
Objective: To introduce a method for tracking results and utilization of...
read it
-
A Survey on the Use of AI and ML for Fighting the COVID-19 Pandemic
Artificial intelligence (AI) and machine learning (ML) have made a parad...
read it
-
Remote health monitoring in the time of COVID-19
Coronavirus disease (COVID-19) is caused by the severe acute respiratory...
read it
-
α-Satellite: An AI-driven System and Benchmark Datasets for Hierarchical Community-level Risk Assessment to Help Combat COVID-19
The novel coronavirus and its deadly outbreak have posed grand challenge...
read it
-
Making Sense of the Robotized Pandemic Response: A Comparison of Global and Canadian Robot Deployments and Success Factors
From disinfection and remote triage, to logistics and delivery, countrie...
read it
The challenges of deploying artificial intelligence models in a rapidly evolving pandemic
The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2, emerged into a world being rapidly transformed by artificial intelligence (AI) based on big data, computational power and neural networks. The gaze of these networks has in recent years turned increasingly towards applications in healthcare. It was perhaps inevitable that COVID-19, a global disease propagating health and economic devastation, should capture the attention and resources of the world's computer scientists in academia and industry. The potential for AI to support the response to the pandemic has been proposed across a wide range of clinical and societal challenges, including disease forecasting, surveillance and antiviral drug discovery. This is likely to continue as the impact of the pandemic unfolds on the world's people, industries and economy but a surprising observation on the current pandemic has been the limited impact AI has had to date in the management of COVID-19. This correspondence focuses on exploring potential reasons behind the lack of successful adoption of AI models developed for COVID-19 diagnosis and prognosis, in front-line healthcare services. We highlight the moving clinical needs that models have had to address at different stages of the epidemic, and explain the importance of translating models to reflect local healthcare environments. We argue that both basic and applied research are essential to accelerate the potential of AI models, and this is particularly so during a rapidly evolving pandemic. This perspective on the response to COVID-19, may provide a glimpse into how the global scientific community should react to combat future disease outbreaks more effectively.
READ FULL TEXT
Comments
There are no comments yet.