0000000000781302
AUTHOR
B. Guidi
Early outcomes and complications following cardiac surgery in patients testing positive for coronavirus disease 2019: An international cohort study
The outbreak of severe acute respiratory syndromecoronavirus-2, the cause of coronavirus disease 2019 (COVID-19) in December 2019 represented a global emergency accounting for more than 2.5 million deaths worldwide.1 It has had an unprecedented influence on cardiac surgery internationally, resulting in cautious delivery of surgery and restructuring of services.2 Understanding the influence of COVID-19 on patients after cardiac surgery is based on assumptions from other surgical specialties and single-center studies. The COVIDSurg Collaborative conducted a multicenter cohort study, including 1128 patients, across 235 hospitals, from 24 countries demonstrating perioperative COVID-19 infection…
Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
The British journal of surgery 108(11), 1274-1292 (2021). doi:10.1093/bjs/znab183
Predicting the availability of users' devices in Decentralized Online Social Networks
The understanding of the user temporal behavior is a crucial aspect for all those systems that rely on user resources for daily operations, such as decentralized online social networks (DOSNs). Indeed, DOSNs exploit the devices of their users to take on and share the tasks needed to provide services such as storing the published data. In the last years, the increasing popularity of DOSN services has changed the way of how people interact with each other by enabling users to connect to these services at any time by using their personal devices (such as notebooks or smartphones). As a result, the availability of data in these systems is strongly affected (or reflected) by the temporal behavio…