Evaluating the plausible application of advanced machine learnings in exploring determinant factors of present pandemic: A case for continent specific COVID-19 analysis

Chakraborti, Suman; Maiti, Arabinda; Pramanik, Suvamoy; Sannigrahi, Srikanta; Pilla, Francesco; Banerjee, Anushna; Das, Dipendra Nath

doi:10.1016/j.scitotenv.2020.142723

Cited by 27 publications

(32 citation statements)

References 62 publications

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“…The resulting data set has been then examined via two advanced supervised machine learning algorithms. The study has found that, among all the explanatory variables, air pollution, migration, economy, and demographic factor have been the most significant controlling factors (Chakraborti et al, 2021).…”

Section: Lessons From the Fieldmentioning

confidence: 96%

AI for development: implications for theory and practice

Bjola¹

2021

Oxford Development Studies

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The arrival of AI technology promises to add a fascinating new chapter to development theory and practice. Current studies have made good progress in examining the potential contributions of AI to achieving sustainable development goals and addressing challenges in specific development areas (poverty, global health, human rights, environment etc.). However, four lessons stand out when considering the impact of future research on the AI/development nexus: learning how to access and combine data from multiple sources, how to master AI techniques to extract analytical insight, how to build socially impactful AI solutions, and how to apply AI to development in an ethically responsible fashion. This paper makes the argument that AI could radically transform development theory and practice by prompting a rethinking of how data and algorithms come together to generate insights into the way in which development challenges are identified, studied, and managed. KEYWORDSArtificial Intelligence; SDGs; machine learning; AI4SG "AI is akin to building a rocket ship. You need a huge engine and a lot of fuel. The rocket engine is the learning algorithms, but the fuel is the huge amounts of data we can feed to these algorithms"

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Section: Lessons From the Fieldmentioning

confidence: 96%

AI for development: implications for theory and practice

Bjola¹

2021

Oxford Development Studies

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“…This method also determines the interconnections among key explanatory variables, COVID-19 case and death counts. The study shows that air pollution has a high impact on COVID-19 casualties [ 10 ]. COVIDetectioNet [ 11 ] is proposed to detect the COVID-19.…”

Section: Introductionmentioning

confidence: 99%

A systematic review on AI/ML approaches against COVID-19 outbreak

Doğan

Tiwari

Jabbar³

et al. 2021

Complex Intell. Syst.

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A pandemic disease, COVID-19, has caused trouble worldwide by infecting millions of people. The studies that apply artificial intelligence (AI) and machine learning (ML) methods for various purposes against the COVID-19 outbreak have increased because of their significant advantages. Although AI/ML applications provide satisfactory solutions to COVID-19 disease, these solutions can have a wide diversity. This increase in the number of AI/ML studies and diversity in solutions can confuse deciding which AI/ML technique is suitable for which COVID-19 purposes. Because there is no comprehensive review study, this study systematically analyzes and summarizes related studies. A research methodology has been proposed to conduct the systematic literature review for framing the research questions, searching criteria and relevant data extraction. Finally, 264 studies were taken into account after following inclusion and exclusion criteria. This research can be regarded as a key element for epidemic and transmission prediction, diagnosis and detection, and drug/vaccine development. Six research questions are explored with 50 AI/ML approaches in COVID-19, 8 AI/ML methods for patient outcome prediction, 14 AI/ML techniques in disease predictions, along with five AI/ML methods for risk assessment of COVID-19. It also covers AI/ML method in drug development, vaccines for COVID-19, models in COVID-19, datasets and their usage and dataset applications with AI/ML.

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“…The pandemic caused by SARS-CoV-2 is of critical concern worldwide. Many places, especially large cities in Europe and the USA, are seriously impacted [15,16]. After the COVID-19 breakout, scientists remain active and focus special attention to this epidemic.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Hazard Rate of Municipalities in Slovakia in Terms of COVID-19

Petrovič

Vilinová

Hilbert

2021

IJERPH

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The coronavirus became a phenomenon in 2020, which is making an unwanted but wide space for the study of various scientific disciplines. The COVID-19 pandemic situation which has reached almost the whole civilized world by its consequences thus offers a unique possibility to analyze the graphic space and the human activities inside it. The aim of this study is to predict and identify the potential rate of threat on the example of COVID-19 in Slovakia through an established model. This model consisted of an assessment of the partial phenomena of exposure, vulnerability, and overall risk. The statistical data used to evaluate these phenomena concerned individual cities in Slovakia. These represent the smallest administrative unit. Indirect methods based on the point method were applied in the paper. The spreading and transfer of the disease was influenced much more by the exposure presented by traffic availability, especially, but also the concentration of inhabitants in the selected locations (shops, cemeteries, and others). In the results, our modeling confirmed the regions with the highest intensity, especially in the districts (Bratislava, Košice, Prešov, and Nitra). The selection of the data and method used in this study together with the results reached and presented may serve as an appropriate tool for the support of decision-making of other measures for the future.

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Evaluating the plausible application of advanced machine learnings in exploring determinant factors of present pandemic: A case for continent specific COVID-19 analysis

Cited by 27 publications

References 62 publications

AI for development: implications for theory and practice

AI for development: implications for theory and practice

A systematic review on AI/ML approaches against COVID-19 outbreak

Analysis of Hazard Rate of Municipalities in Slovakia in Terms of COVID-19

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