How Artificial Intelligence and New Technologies Can Help the Management of the COVID-19 Pandemic.
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TLDR
In this article, a narrative review of the adoption of artificial intelligence and new technologies in the management of pandemics and communicable diseases such as SARS-CoV-2 is presented.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.read more
Citations
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Artificial Intelligence in Digital Pathology: What Is the Future? Part 2: An Investigation on the Insiders
TL;DR: In this paper, an electronic survey based on the standardized package Microsoft Forms (Microsoft, Redmond, WA, USA) was proposed to a sample of biomedical laboratory technicians (149 admitted in the study, 76 males, 73 females, mean age 44.2 years).
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Legal and Regulatory Framework for AI Solutions in Healthcare in EU, US, China, and Russia: New Scenarios after a Pandemic
TL;DR: In this paper, a global effort is needed for an open, mature conversation about the best possible way to guard against and mitigate possible harms to realize the potential of AI across health systems in a respectful and ethical way.
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The RALE Score Versus the CT Severity Score in Invasively Ventilated COVID-19 Patients—A Retrospective Study Comparing Their Prognostic Capacities
Christel M.A. Valk,Claudio Zimatore,Guido Mazzinari,Charalampos Pierrakos,Chaisith Sivakorn,Jutamas Dechsanga,Salvatore Grasso,Ludo F. M. Beenen,Lieuwe D. J. Bos,Frederique Paulus,Marcus J. Schultz,Luigi Pisani +11 more
TL;DR: Only CTSS was associated with ICU mortality in a cohort of invasively ventilated patients with acute respiratory distress syndrome due to COVID-19 despite poor prognostic capacity.
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Development and Validation of a Multimodal-Based Prognosis and Intervention Prediction Model for COVID-19 Patients in a Multicenter Cohort
Jeonghoon Lee,J. S. Ahn,Myung Jin Chung,Yeon Joo Jeong,Jin Hwan Kim,Jae-Kwang Lim,Jin Young Kim,Young Jae Kim,Jong Eun Lee,Eun Young Kim +9 more
TL;DR: It is shown that a multimodal AI model can improve the performance of predicting both the prognosis and intervention in COVID-19 patients, and this could assist in effective treatment and subsequent resource management.
References
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Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing.
Luca Ferretti,Chris Wymant,Michelle Kendall,Lele Zhao,Anel Nurtay,Lucie Abeler-Dörner,Michael Parker,David Bonsall,Christophe Fraser +8 more
TL;DR: A mathematical model for infectiousness was developed to estimate the basic reproductive number R0 and to quantify the contribution of different transmission routes and the requirements for successful contact tracing, and the combination of two key parameters needed to reduce R0 to less than 1 was determined.
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Isolation, quarantine, social distancing and community containment: pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak.
TL;DR: Public health measures were decisive in controlling the SARS epidemic in 2003 but whether these measures will be sufficient to control 2019-nCoV depends on addressing some unanswered questions.
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A global database of COVID-19 vaccinations.
Edouard Mathieu,Hannah Ritchie,Esteban Ortiz-Ospina,Max Roser,Joe Hasell,Cameron Appel,Charles M. Giattino,Lucas Rodés-Guirao +7 more
TL;DR: The Our World in Data COVID-19 dataset as mentioned in this paper is a global public dataset that tracks the scale and rate of the vaccine rollout across the world and includes data on the total number of vaccinations administered, first and second doses administered, daily vaccination rates and population-adjusted coverage for all countries for which data are available.
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Can we contain the COVID-19 outbreak with the same measures as for SARS?
TL;DR: COVID-19 differs from SARS in terms of infectious period, transmissibility, clinical severity, and extent of community spread, but even if traditional public health measures are not able to fully contain the outbreak of CO VID-19, they will still be effective in reducing peak incidence and global deaths.
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Interventions for improving the adoption of shared decision making by healthcare professionals
Dawn Stacey,Stéphane Turcotte,Marie-Joëlle Cossi,Jennifer Kryworuchko,Ian D. Graham,Anne Lyddiatt,Mary C. Politi,Richard Thomson,Glyn Elwyn,Norbert Donner-Banzhoff +9 more
TL;DR: It is uncertain whether interventions to improve adoption of SDM are effective given the low quality of the evidence, but any intervention that actively targets patients, healthcare professionals, or both, is better than none.