How Artificial Intelligence and New Technologies Can Help the Management of the COVID-19 Pandemic

Abstract

The COVID-19 pandemic has worked as a catalyst, pushing governments, private companies, and healthcare facilities to design, develop, and adopt innovative solutions to control it, as is often the case when people are driven by necessity. After 18 months since the first case, it is time to think about the pros and cons of such technologies, including artificial intelligence—which is probably the most complex and misunderstood by non-specialists—in order to get the most out of them, and to suggest future improvements and proper adoption. The aim of this narrative review was to select the relevant papers that directly address the adoption of artificial intelligence and new technologies in the management of pandemics and communicable diseases such as SARS-CoV-2: environmental measures; acquisition and sharing of knowledge in the general population and among clinicians; development and management of drugs and vaccines; remote psychological support of patients; remote monitoring, diagnosis, and follow-up; and maximization and rationalization of human and material resources in the hospital environment.

Artificial Intelligence in Digital Pathology: What Is the Future? Part 2: An Investigation on the Insiders

“…The COVID-19 pandemic has also highlighted the broad-spectrum potential of AI . In a recent review [ 26 ], for example, relevant papers were selected that address the adoption of artificial intelligence and new technologies in the management of pandemics and communicable diseases such as SARS-CoV-2.…”

“…The three illustrated potentials [ 25 , 26 , 27 ] are also important in DP. In fact, in DP, the need for categorizing images merges with the need to make decisions and/or deduce approaches through actions on large databases and data sets or with other needs not based on medical images [ 1 , 19 , 20 ].…”

“…Therefore, the need and the justification of studies such as ours that tackle the introduction of AI focusing on acceptance and with a broad approach clearly emerges from these articles [ 25 , 26 , 27 ] .…”

Development and Validation of a Multimodal-Based Prognosis and Intervention Prediction Model for COVID-19 Patients in a Multicenter Cohort

“…It has been shown that AI can help interpret CXRs effectively in COVID-19 patients [16]. Khuzani et al showed that a CXR AI classifier trained on 420 images can accurately classify, with 94% accuracy, the CXR images into normal, COVID-19 and non-COVID-19 pneumonia, based on imaging findings alone [17]. Naturally, combining different modes of data used in clinical medicine to predict the events in COVID-19 patients has become the goal of many researchers.…”

Legal and Regulatory Framework for AI Solutions in Healthcare in EU, US, China, and Russia: New Scenarios after a Pandemic

“…In the last two years, new technologies such as AI proved helpful in the management of the COVID-19 pandemic [12][13][14][15][16][17][18]. During the first months of 2020, chest computedtomography scans showed the extent of lung damage caused by COVID-19; accordingly, efforts were established around the world to facilitate data sharing, model training, and scan assessment [10,15].…”