scholarly journals The Artificial Intelligence (AI) during COVID-19 Pandemic

2021 ◽  
Vol 1 (1) ◽  
pp. 3-5
Author(s):  
Binta Suleman Abdullahi ◽  
Faisal Muhammad
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Data Science ◽  
Health Issue ◽  
Global Public Health ◽  
Health Crisis ◽  
Public Health Crisis

The coronavirus disease 2019 (COVID-19) pandemic is the twenty-first century's first global public health crisis. Currently, a variety of AI-powered initiatives based on data science, "machine learning," or "big data," are being employed in a variety of disciplines to forecast, explain, and manage the various scenarios produced by the health issue.

Synergising International Public Health Law and International Disaster Law

2020 ◽  
pp. 1-11
Author(s):  
Pratik DIXIT
Keyword(s):  
Public Health ◽  
International Health ◽  
Health Law ◽  
Global Public Health ◽  
Public Health Law ◽  
Health Crisis ◽  
Response Strategies ◽  
Public Health Crisis ◽  
International Public Health ◽  
Health Regulations

There is no time more opportune to review the workings of the International Health Regulations (IHR) than the present COVID-19 crisis. This article analyses the theoretical and practical aspects of international public health law (IPHL), particularly the IHR, to argue that it is woefully unprepared to protect human rights in times of a global public health crisis. To rectify this, the article argues that the IHR should design effective risk reduction and response strategies by incorporating concepts from international disaster law (IDL). Along similar lines, this article suggests that IDL also has a lot to learn from IPHL in terms of greater internationalisation and institutionalisation. Institutionalisation of IDL on par with IPHL will provide it with greater legitimacy, transparency and accountability. This article argues that greater cross-pollination of ideas between IDL and IPHL is necessary in order to make these disciplines more relevant for the future.

scholarly journals Leveraging Artificial Intelligence and Big Data to Optimize COVID-19 Clinical Public Health and Vaccination Roll-Out Strategies in Africa

2021 ◽  
Vol 18 (15) ◽  
pp. 7890
Author(s):  
Bruce Mellado ◽  
Jianhong Wu ◽  
Jude Dzevela Kong ◽  
Nicola Luigi Bragazzi ◽  
Ali Asgary ◽  
...  
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Developed Countries ◽  
Machine Learning Techniques ◽  
Multiple Data ◽  
Learning Techniques ◽  
Unequal Access ◽  
Roll Out

COVID-19 is imposing massive health, social and economic costs. While many developed countries have started vaccinating, most African nations are waiting for vaccine stocks to be allocated and are using clinical public health (CPH) strategies to control the pandemic. The emergence of variants of concern (VOC), unequal access to the vaccine supply and locally specific logistical and vaccine delivery parameters, add complexity to national CPH strategies and amplify the urgent need for effective CPH policies. Big data and artificial intelligence machine learning techniques and collaborations can be instrumental in an accurate, timely, locally nuanced analysis of multiple data sources to inform CPH decision-making, vaccination strategies and their staged roll-out. The Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC) has been established to develop and employ machine learning techniques to design CPH strategies in Africa, which requires ongoing collaboration, testing and development to maximize the equity and effectiveness of COVID-19-related CPH interventions.

Data Science: Big Data, Machine Learning, and Artificial Intelligence

2018 ◽  
Vol 15 (3) ◽  
pp. 497-498 ◽  
Author(s):  
Ruth C. Carlos ◽  
Charles E. Kahn ◽  
Safwan Halabi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Data Science

Big Data and Machine Learning

2018 ◽  
pp. 225-239
Author(s):  
Fernando Enrique Lopez Martinez ◽  
Edward Rolando Núñez-Valdez
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Complete Solution ◽  
Big Data Analytics ◽  
Machine Learning Algorithms ◽  
Data Sets ◽  
Healthcare Organizations ◽  
High Level

IoT, big data, and artificial intelligence are currently three of the most relevant and trending pieces for innovation and predictive analysis in healthcare. Many healthcare organizations are already working on developing their own home-centric data collection networks and intelligent big data analytics systems based on machine-learning principles. The benefit of using IoT, big data, and artificial intelligence for community and population health is better health outcomes for the population and communities. The new generation of machine-learning algorithms can use large standardized data sets generated in healthcare to improve the effectiveness of public health interventions. A lot of these data come from sensors, devices, electronic health records (EHR), data generated by public health nurses, mobile data, social media, and the internet. This chapter shows a high-level implementation of a complete solution of IoT, big data, and machine learning implemented in the city of Cartagena, Colombia for hypertensive patients by using an eHealth sensor and Amazon Web Services components.

Bhutan: The Role of the Constitutional Monarch in a Public Health Crisis

2021 ◽  
pp. 279-292
Author(s):  
Sonam Tshering ◽  
Nima Dorji
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Health Crisis ◽  
Drug Smuggling ◽  
Personal Involvement ◽  
Public Health Crisis ◽  
The People ◽  
Long Run ◽  
The Government

This chapter reflects on Bhutan’s response to the Covid-19 pandemic. The people’s trust and confidence in the leadership of His Majesty the King, their government, strong Buddhist values to help each other, and the conscience of unity and solidarity proved their foremost strength in containing this pandemic as a nation. The king’s personal involvement helped guide, motivate, and encourage compliance with and support for the government’s response. However, Bhutan faced several challenges during the pandemic. Though most of the people are united, there are outliers who took advantage of the situation; there are reported cases of drug smuggling and one case of a person who escaped from quarantine. The government responded by increasing border patrols. In the long run, other solutions could be considered: installing a smart wall—using drones, sensors, and artificial intelligence patrols—would give Bhutan more control over its borders in the context of another epidemic while also enabling the government to better control smuggling.

scholarly journals Coronavirus Pandemic: a major public health crisis for the developed and developing world

2021 ◽  
Vol 15 (03) ◽  
pp. 366-369
Author(s):  
Rooh Ullah ◽  
Muhammad Suleman Rana ◽  
Mehmood Qadir ◽  
Muhammad Usman ◽  
Niaz Ahmed
Keyword(s):  
Public Health ◽  
Severe Acute Respiratory Syndrome ◽  
Viral Infection ◽  
The Novel ◽  
Global Public Health ◽  
Health Crisis ◽  
Public Health Crisis ◽  
The World ◽  
Novel Coronavirus ◽  
Day By Day

Pandemic of novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections in China is now become global public health crisis. At present 87.64% of the world is infected by this deadly illness. The risk from this epidemic depends on the nature of the virus, including how well it transmits from person to person, and the complications resulting from this current illness. The novel coronavirus has killed thousands of people in China and other countries as well; its rate of mortality is increasing day by day. There is an urgent need to control the virus by developing vaccine or any other antiviral drugs to save the world from this deadly viral infection.

scholarly journals Unlocking the Power of Artificial Intelligence and Big Data in Medicine

10.2196/16607 ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. e16607 ◽  
Author(s):  
Christian Lovis
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Decision Support ◽  
Data Science ◽  
Global Environment ◽  
Data Driven ◽  
Cross Linking ◽  
Science And Society ◽  
Slowing Down

Data-driven science and its corollaries in machine learning and the wider field of artificial intelligence have the potential to drive important changes in medicine. However, medicine is not a science like any other: It is deeply and tightly bound with a large and wide network of legal, ethical, regulatory, economical, and societal dependencies. As a consequence, the scientific and technological progresses in handling information and its further processing and cross-linking for decision support and predictive systems must be accompanied by parallel changes in the global environment, with numerous stakeholders, including citizen and society. What can be seen at the first glance as a barrier and a mechanism slowing down the progression of data science must, however, be considered an important asset. Only global adoption can transform the potential of big data and artificial intelligence into an effective breakthroughs in handling health and medicine. This requires science and society, scientists and citizens, to progress together.

scholarly journals Renal Transplants In Covid-19 Pandemic

2020 ◽  
Vol 6 (2) ◽  
pp. 1-4
Author(s):  
Keyword(s):  
Public Health ◽  
Kidney Transplant ◽  
Global Public Health ◽  
Transplant Recipients ◽  
Kidney Transplant Recipients ◽  
Renal Transplants ◽  
Health Crisis ◽  
Public Health Crisis

Coronavirus Disease 2019 (COVID-19) is a global public health crisis and a pandemic of international concern. The delivery of transplant care worldwide is severely challenged by the COVID-19 pandemic. Along with the inherent risks of immunosuppression, kidney transplant recipients are also at higher risk of getting infected with the coronavirus.

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