scholarly journals Data-Driven Analytics Leveraging Artificial Intelligence in the Era of COVID-19: An Insightful Review of Recent Developments

Symmetry ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 16
Author(s):  
Abdul Majeed ◽  
Seong Oun Hwang
Keyword(s):  
Artificial Intelligence ◽  
Personal Data ◽  
General Purpose ◽  
Data Driven ◽  
Healthcare Sector ◽  
Future Research ◽  
Recent Developments ◽  
Technological Developments ◽  
Novel Coronavirus

This paper presents the role of artificial intelligence (AI) and other latest technologies that were employed to fight the recent pandemic (i.e., novel coronavirus disease-2019 (COVID-19)). These technologies assisted the early detection/diagnosis, trends analysis, intervention planning, healthcare burden forecasting, comorbidity analysis, and mitigation and control, to name a few. The key-enablers of these technologies was data that was obtained from heterogeneous sources (i.e., social networks (SN), internet of (medical) things (IoT/IoMT), cellular networks, transport usage, epidemiological investigations, and other digital/sensing platforms). To this end, we provide an insightful overview of the role of data-driven analytics leveraging AI in the era of COVID-19. Specifically, we discuss major services that AI can provide in the context of COVID-19 pandemic based on six grounds, (i) AI role in seven different epidemic containment strategies (a.k.a non-pharmaceutical interventions (NPIs)), (ii) AI role in data life cycle phases employed to control pandemic via digital solutions, (iii) AI role in performing analytics on heterogeneous types of data stemming from the COVID-19 pandemic, (iv) AI role in the healthcare sector in the context of COVID-19 pandemic, (v) general-purpose applications of AI in COVID-19 era, and (vi) AI role in drug design and repurposing (e.g., iteratively aligning protein spikes and applying three/four-fold symmetry to yield a low-resolution candidate template) against COVID-19. Further, we discuss the challenges involved in applying AI to the available data and privacy issues that can arise from personal data transitioning into cyberspace. We also provide a concise overview of other latest technologies that were increasingly applied to limit the spread of the ongoing pandemic. Finally, we discuss the avenues of future research in the respective area. This insightful review aims to highlight existing AI-based technological developments and future research dynamics in this area.

scholarly journals Out of the loop? On the radical and the routine in urban big data

Urban Studies ◽  
2021 ◽  
pp. 004209802110140
Author(s):  
Sarah Barns
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Computational Models ◽  
Data Driven ◽  
Urban Systems ◽  
Out Of The Loop ◽  
Urban Futures ◽  
Urban Behaviour ◽  
The City

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.

Artificial Intelligence Applications for Industry 4.0: A Literature-Based Study

2021 ◽  
pp. 1-29
Author(s):  
Mohd Javaid ◽  
Abid Haleem ◽  
Ravi Pratap Singh ◽  
Rajiv Suman
Keyword(s):  
Artificial Intelligence ◽  
Industry 4.0 ◽  
Decisive Role ◽  
Vital Role ◽  
Data Types ◽  
Process Data ◽  
Automation Systems ◽  
Recent Developments ◽  
Iot Devices

Artificial intelligence (AI) contributes to the recent developments in Industry 4.0. Industries are focusing on improving product consistency, productivity and reducing operating costs, and they want to achieve this with the collaborative partnership between robotics and people. In smart industries, hyperconnected manufacturing processes depend on different machines that interact using AI automation systems by capturing and interpreting all data types. Smart platforms of automation can play a decisive role in transforming modern production. AI provides appropriate information to take decision-making and alert people of possible malfunctions. Industries will use AI to process data transmitted from the Internet of things (IoT) devices and connected machines based on their desire to integrate them into their equipment. It provides companies with the ability to track their entire end-to-end activities and processes fully. This literature review-based paper aims to brief the vital role of AI in successfully implementing Industry 4.0. Accordingly, the research objectives are crafted to facilitate researchers, practitioners, students and industry professionals in this paper. First, it discusses the significant technological features and traits of AI, critical for Industry 4.0. Second, this paper identifies the significant advancements and various challenges enabling the implementation of AI for Industry 4.0. Finally, the paper identifies and discusses significant applications of AI for Industry 4.0. With an extensive review-based exploration, we see that the advantages of AI are widespread and the need for stakeholders in understanding the kind of automation platform they require in the new manufacturing order. Furthermore, this technology seeks correlations to avoid errors and eventually to anticipate them. Thus, AI technology is gradually accomplishing various goals of Industry 4.0.

scholarly journals Critical Care, Critical Data

2019 ◽  
Vol 10 ◽  
pp. 117959721985656 ◽  
Author(s):  
Christopher V Cosgriff ◽  
Leo Anthony Celi ◽  
David J Stone
Keyword(s):  
Artificial Intelligence ◽  
Critical Care ◽  
Clinical Data ◽  
Continuous Monitoring ◽  
Data Science ◽  
Clinical Decision ◽  
Critical Care Medicine ◽  
Data Driven ◽  
Critical Data

As big data, machine learning, and artificial intelligence continue to penetrate into and transform many facets of our lives, we are witnessing the emergence of these powerful technologies within health care. The use and growth of these technologies has been contingent on the availability of reliable and usable data, a particularly robust resource in critical care medicine where continuous monitoring forms a key component of the infrastructure of care. The response to this opportunity has included the development of open databases for research and other purposes; the development of a collaborative form of clinical data science intended to fully leverage these data resources, and the creation of data-driven applications for purposes such as clinical decision support. Most recently, data levels have reached the thresholds required for the development of robust artificial intelligence features for clinical purposes. The systematic capture and analysis of clinical data in both individuals and populations allows us to begin to move toward precision medicine in the intensive care unit (ICU). In this perspective review, we examine the fundamental role of data as we present the current progress that has been made toward an artificial intelligence (AI)-supported, data-driven precision critical care medicine.

scholarly journals Emotional Expression of #body on Instagram

2020 ◽  
Vol 6 (2) ◽  
pp. 205630512092477 ◽  
Author(s):  
Clelia Malighetti ◽  
Simona Sciara ◽  
Alice Chirico ◽  
Giuseppe Riva
Keyword(s):  
Artificial Intelligence ◽  
Body Image ◽  
Emotional Expression ◽  
Image Representation ◽  
Future Research ◽  
Discrete Emotions ◽  
Emotional Model ◽  
Artificial Intelligence Technology ◽  
Program Interface

Our aim was to explore emotions in Instagram images marked with hashtags referring to body image–related components using an artificial intelligence–based discrete emotional analysis. A total of 500 Instagram photos marked by specific hashtags related to body image components were analyzed and specific discrete emotions expressed in each picture were detected using the Emotion application program interface API from Microsoft Azure Cognitive Service. Results showed that happiness and neutrality were the most intense and recognizable emotions expressed in all images. Happiness intensity was significantly higher in images with #bodyimage and #bodyconfidence and higher levels of neutral emotion were found in images tagged with #body, #bodyfitness, and #thininspirational. This study integrated a discrete emotional model with the conventional dimensional one, and offered a higher degree of granularity in the analysis of emotions–body link on Instagram through an artificial intelligence technology. Future research should deepen the use of discrete emotions on Instagram and the role of neutrality in body image representation.

scholarly journals Artificial Intelligence in Strategizing: Prospects and Challenges

2021 ◽  
pp. 625-646
Author(s):  
Georg von Krogh ◽  
Shiko M. Ben-Menahem ◽  
Yash Raj Shrestha
Keyword(s):  
Artificial Intelligence ◽  
Strategy Implementation ◽  
Future Research ◽  
Strategic Analysis ◽  
Related Research ◽  
Strategic Processes ◽  
Strategy Process ◽  
Recent Developments ◽  
Two Stages ◽  
Key Questions

Recent developments in the theory and research on artificial intelligence (AI) hold great promises as well as challenges for the strategist’s core activities and conduct of strategic processes. These promises and challenges require the strategy field to both reevaluate some of the principal assumptions and implications of strategizing. This chapter takes stock of research on AI applied to strategizing and illustrates what we believe are key questions for future research on the strategy-AI nexus. The chapter discusses the potential of AI in two stages in the strategy process: strategic analysis and formulation, as well as strategy implementation. The aim of this chapter is to engage strategy scholars in advancing AI-related research on strategizing.

scholarly journals National approaches towards implementation of artificial intelligence: Singapore’s experience

2020 ◽  
pp. 62-73
Author(s):  
Ella Gorian
Keyword(s):  
Artificial Intelligence ◽  
Private Sector ◽  
Self Regulation ◽  
National Level ◽  
Personal Data ◽  
Role Of Government ◽  
Normative Documents ◽  
Personal Data Protection ◽  
The Government

The object of this research is the relations in the area of implementation of artificial intelligence technologies. The subject of this research is the normative documents of Singapore that establish requirements towards development and application of artificial intelligence technologies. The article determines the peculiarities of Singaporean approach towards regulation of relations in the indicated sphere. Characteristic is given to the national initiative and circle of actors involved in the development and realization of normative provisions with regards to implementation of digital technologies. The author explores the aspects of private public partnership, defines the role of government in regulation of relation, as well as gives special attention to the question of ensuring personal data protection used by the artificial intelligence technologies. Positive practices that can be utilized in Russian strategy for the development of artificial intelligence are described. Singapore applies the self-regulation approach towards the processes of implementation of artificial intelligence technologies, defining the backbone role of the government, establishing common goals, and involving representative of private sector and general public. Moreover, the government acts as the guarantor of meeting the interests of private sector by creating an attractive investment regime and citizens, setting strict requirements with regards to data usage and control over the artificial intelligence technologies. A distinguishing feature of Singaporean approach consists in determination of the priority sectors of economy and instruments of ensuring systematicity in implementation of artificial intelligence. Singapore efficiently uses its demographic and economic peculiarities for proliferation of the technologies of artificial intelligence in Asian Region; the developed and successfully tested on the national level model of artificial intelligence management received worldwide recognition and application. Turning Singapore into the international center of artificial intelligence is also instigated by the improvement of legal regime with simultaneous facilitation in the sphere of intellectual property. These specificities should be taken into account by the Russian authors of national strategy for the development of artificial intelligence.

scholarly journals COVID-19 Contact Tracing: Challenges and Future Directions

2020 ◽  
Author(s):  
Mohammad Jabed Morshed Chowdhury ◽  
Md Sadek Ferdous ◽  
Kamanashis Biswas ◽  
Niaz Chowdhury ◽  
Vallipuram Muthukkumarasamy
Keyword(s):  
Personal Data ◽  
Human Memory ◽  
Data Driven ◽  
Contact Tracing ◽  
Future Directions ◽  
Significant Challenge ◽  
Innovative Solution ◽  
Public Health Officials ◽  
Novel Coronavirus ◽  
High Level

Contact tracing has become a vital tool for public health officials to effectively combat the spread of new diseases, such asthe novel coronavirus disease COVID-19. Contact tracing is not new to epidemiologist rather, it used manual or semi-manualapproaches that are incredibly time-consuming, costly and inefficient. It mostly relies on human memory while scalabilityis a significant challenge in tackling pandemics. The unprecedented health and socio-economic impacts led researchersand practitioners around the world to search for technology-based approaches for providing scalable and timely answers.Smartphones and associated digital technologies have the potential to provide a better approach due to their high level ofpenetration, coupled with mobility. While data-driven solutions are extremely powerful, the fear among citizens is thatinformation like location or proximity associated with other personal data and can be weaponised by the states to enforcesurveillance. Low adoption rate of such apps due to the lack of trust questioned the efficacy and demanded researchers tofind innovative solution for building digital-trust, and appropriately balancing privacy and accuracy of data. In this paper,we have critically reviewed such protocols and apps to identify the strength and weakness of each approach. Finally, wehave penned down our recommendations to make the future contact tracing mechanisms more universally inter-operable andprivacy-preserving.

scholarly journals Current and emerging artificial intelligence applications for pediatric musculoskeletal radiology

2021 ◽  
Author(s):  
Amaka C. Offiah
Keyword(s):  
Artificial Intelligence ◽  
Pediatric Radiology ◽  
Bone Age ◽  
Future Research ◽  
Fracture Detection ◽  
Musculoskeletal Radiology ◽  
Age Assessment ◽  
Adult World ◽  
Bone Age Assessment

AbstractArtificial intelligence (AI) is playing an ever-increasing role in radiology (more so in the adult world than in pediatrics), to the extent that there are unfounded fears it will completely take over the role of the radiologist. In relation to musculoskeletal applications of AI in pediatric radiology, we are far from the time when AI will replace radiologists; even for the commonest application (bone age assessment), AI is more often employed in an AI-assist mode rather than an AI-replace or AI-extend mode. AI for bone age assessment has been in clinical use for more than a decade and is the area in which most research has been conducted. Most other potential indications in children (such as appendicular and vertebral fracture detection) remain largely in the research domain. This article reviews the areas in which AI is most prominent in relation to the pediatric musculoskeletal system, briefly summarizing the current literature and highlighting areas for future research. Pediatric radiologists are encouraged to participate as members of the research teams conducting pediatric radiology artificial intelligence research.

SIGNIFICANT ROLE OF AI & ML TECHNIQUES USED IN IMPROVEMENT OF CYBER SECURITY

2021 ◽  
Vol 12 (1) ◽  
pp. 80-89
Author(s):  
Muskan Kumari ◽  
Keyword(s):  
Artificial Intelligence ◽  
Cyber Security ◽  
Cyber Attacks ◽  
Current Status ◽  
Future Research ◽  
Engineering Managers ◽  
Network Protection ◽  
Machine Leaning ◽  
Expert Community

Cyber Security has become an arising challenge for business information system in current era. AI (Artificial Intelligence) is broadly utilized in various field, however it is still generally new in cyber security. Nonetheless, the applications in network protection are significant for everybody`s day by day life. In this paper, we present the current status of AI in cyber security field, and afterward portray a few contextual investigations and uses of AI to help the community including engineering managers, teachers, educators, business people, and understudies to more readily comprehend this field, for example, the difficulties and uncertain issues of AI in online protection. According to the new challenges, the expert community has two main approaches: to adopt the philosophy and methods of Military Intelligence, and to use Artificial Intelligence methods for counteraction of Cyber Attacks. Cyber security is a vital danger for any business as the quantity of attacks is expanding. Developing of attacks on cyber security is undermining our reality. AI (Artificial Intelligence) and ML (Machine Leaning) can help identify dangers and give proposals to cyber Analyst. Advancement of appropriation of AI/ML applied to cyber security requires banding together of industry, the scholarly community, and government on a worldwide scale. We also discuss future research opportunities associated with the development of AI techniques in the cyber security ?eld across a scope of utilization areas.

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