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- Drake, TM, et al.
(författare)
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Surgical site infection after gastrointestinal surgery in children: an international, multicentre, prospective cohort study
- 2020
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Ingår i: BMJ global health. - : BMJ. - 2059-7908. ; 5:12
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Tidskriftsartikel (refereegranskat)abstract
- Surgical site infection (SSI) is one of the most common healthcare-associated infections (HAIs). However, there is a lack of data available about SSI in children worldwide, especially from low-income and middle-income countries. This study aimed to estimate the incidence of SSI in children and associations between SSI and morbidity across human development settings.MethodsA multicentre, international, prospective, validated cohort study of children aged under 16 years undergoing clean-contaminated, contaminated or dirty gastrointestinal surgery. Any hospital in the world providing paediatric surgery was eligible to contribute data between January and July 2016. The primary outcome was the incidence of SSI by 30 days. Relationships between explanatory variables and SSI were examined using multilevel logistic regression. Countries were stratified into high development, middle development and low development groups using the United Nations Human Development Index (HDI).ResultsOf 1159 children across 181 hospitals in 51 countries, 523 (45·1%) children were from high HDI, 397 (34·2%) from middle HDI and 239 (20·6%) from low HDI countries. The 30-day SSI rate was 6.3% (33/523) in high HDI, 12·8% (51/397) in middle HDI and 24·7% (59/239) in low HDI countries. SSI was associated with higher incidence of 30-day mortality, intervention, organ-space infection and other HAIs, with the highest rates seen in low HDI countries. Median length of stay in patients who had an SSI was longer (7.0 days), compared with 3.0 days in patients who did not have an SSI. Use of laparoscopy was associated with significantly lower SSI rates, even after accounting for HDI.ConclusionThe odds of SSI in children is nearly four times greater in low HDI compared with high HDI countries. Policies to reduce SSI should be prioritised as part of the wider global agenda.
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| 3. |
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Deep Learning in Computer Vision : Principles and Applications
- 2020. - 1st
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Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
- Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, for postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition.
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| 5. |
- Mamdouh, Moustafa, et al.
(författare)
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Outlook on Security and Privacy in IoHT : Key Challenges and Future Vision
- 2020
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Ingår i: Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020). - Cham : Springer. - 9783030442880 - 9783030442897 ; , s. 721-730
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The Internet of Things (IoT) security and privacy have received considerable research attention due to the IoT applicability in various domains. IoT systems have several applications, such as smart homes, smart cities, e-Health, industry, agriculture, and environmental monitoring. One of the most important applications is the Internet of Healthcare Things (IoHT) because it helps humans and patients obtain rapid diagnoses, remote monitoring, and home rehabilitation. IoHT security can be classified into four categories: applications, architecture, communication, and data security. This paper presents a short, but focused, review on IoHT security and privacy. It also explores recent security algorithms and protocols that are used to secure personal patient data, clinicians, and healthcare information. The future vision of IoHT challenges and countermeasures is given at the end of this study. Blockchain healthcare technology provides secure digital payment and privileged data access.
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| 6. |
- Masmoudi, Fatma, et al.
(författare)
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A Guiding Framework for Vetting the Internet of Things
- 2020
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Ingår i: Journal of Information Security and Applications. - : Elsevier. - 2214-2134 .- 2214-2126. ; 55
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Tidskriftsartikel (refereegranskat)abstract
- Like any emerging and disruptive technology, multiple obstacles are slowing down the Internet of Things (IoT) expansion for instance, multiplicity of things’ standards, users’ reluctance and sometimes rejection due to privacy invasion, and limited IoT platform interoperability. IoT expansion is also accompanied by the widespread use of mobile apps supporting anywhere, anytime service provisioning to users. By analogy to vetting mobile apps, this paper addresses the lack of principles and techniques for vetting IoT devices (things) in preparation for their integration into mission-critical systems. Things have got vulnerabilities that should be discovered and assessed through proper device vetting. Unfortunately, this is not happening. Rather than sensing a nuclear turbines steam level, a thing could collect some sensitive data about the turbine without the knowledge of users and leak these data to third parties. This paper presents a guiding framework that defines the concepts of, principles of, and techniques for thing vetting as a pro-active response to potential things vulnerabilities.
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