scholarly journals Relevance and the Dissemination of Medical Literature in the Information Age

2018 ◽  
Vol 13 (1) ◽  
pp. 22
Author(s):  
Frank J Kaszuba ◽  
W Michael Alberts
Keyword(s):  
Artificial Intelligence ◽  
Exponential Growth ◽  
Search Engines ◽  
Medical Literature ◽  
Information Age ◽  
Healthcare Providers ◽  
Medical Data ◽  
Informed Decisions ◽  
The Future

The exponential growth of medical data can be difficult to process. Healthcare providers must be critical in their evaluation of information, but at the same time be ready to question long-held beliefs. At present, major search engines and aggregators are inadequate at determining relevance and significance of this vast body of data. In the future, artificial intelligence may be able to filter useful data and present it in a meaningful fashion, allowing us to make informed decisions.

scholarly journals Artificial Neural Network Blockchain Techniques for Healthcare System: Focusing on the Personal Health Records

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 763
Author(s):  
Seong-Kyu Kim ◽  
Jun-Ho Huh
Keyword(s):  
Artificial Intelligence ◽  
Data Transmission ◽  
Industrial Revolution ◽  
Medical Data ◽  
Personal Health Records ◽  
Personal Health ◽  
Health Records ◽  
Fourth Industrial Revolution ◽  
The Future ◽  
And Performance

This paper seeks to use artificial intelligence blockchain algorithms to ensure safe verification of medical institution PHR data and accurate verification of medical data as existing vulnerabilities. Artificial intelligence has recently spread and has led to research on many technologies thanks to the Fourth Industrial Revolution. This is a very important factor in healthcare as well as the healthcare industry’s position. Likewise, blockchain is very safe to apply because it encrypts and verifies these medical data in case they are hacked or leaked. These technologies are considered very important. This study raises the problems of these artificial intelligence blockchains and recognizes blockchain, artificial intelligence, neural networks, healthcare, etc.; these problems clearly exist, so systems like EHR are not being used. In the future, ensuring privacy will be made easier when these EHRs are activated and data transmission and data verification between hospitals are completed. To overcome these shortcomings, we define an information security blockchain artificial intelligence framework and verify blockchain systems for accurate extraction, storage, and verification of data. In addition, various verification and performance evaluation indicators are set to obtain the TPS of medical data and for the implementation of standardization work in the future. This paper seeks to maximize the confidentiality of blockchain and the sensitivity and availability of artificial intelligence.

scholarly journals Regulatory responses to medical machine learning

2020 ◽  
Author(s):  
Timo Minssen ◽  
Sara Gerke ◽  
Mateo Aboy ◽  
Nicholson Price ◽  
Glenn Cohen
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Privacy ◽  
Healthcare Providers ◽  
Medical Data ◽  
Training Set ◽  
International Context ◽  
International Perspectives ◽  
The Usa ◽  
New Applications

Abstract Companies and healthcare providers are developing and implementing new applications of medical artificial intelligence, including the artificial intelligence sub-type of medical machine learning (MML). MML is based on the application of machine learning (ML) algorithms to automatically identify patterns and act on medical data to guide clinical decisions. MML poses challenges and raises important questions, including (1) How will regulators evaluate MML-based medical devices to ensure their safety and effectiveness? and (2) What additional MML considerations should be taken into account in the international context? To address these questions, we analyze the current regulatory approaches to MML in the USA and Europe. We then examine international perspectives and broader implications, discussing considerations such as data privacy, exportation, explanation, training set bias, contextual bias, and trade secrecy.

scholarly journals Impact of Renewable Energy Utilization and Artificial Intelligence in Achieving Sustainable Development Goals

2021 ◽  
Author(s):  
M Hannan ◽  
Ali Al-Shetwi ◽  
R Begum ◽  
Pin Ker ◽  
M Mansor ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Sustainable Development ◽  
Renewable Energy ◽  
Exponential Growth ◽  
Sustainable Development Goals ◽  
Expert Elicitation ◽  
Energy Utilization ◽  
The World ◽  
The Future ◽  
Development Goals

Abstract Many countries around the world are planning to reach 100% renewable energy (RE) use by 2050. In this context and due to the recent sharp increase in RE utilization in the global energy mix along with its progressive impact on the world energy sector, the evaluation and investigation of its effect on achieving sustainable development goals (SDGs) are not covered sufficiently. Here, we present an assessment of the emerging role of RE utilization and artificial intelligence (AI) toward achieving SDGs. A total of 17 SDGs were divided into three groups, namely, environment, society, and economy, as per the three key pillars of sustainable development. The RE has a positive impact toward achieving 75 targets across all SDGs by using an expert elicitation method-based consensus. However, it may negatively affect the accomplishment of the 27 targets. In addition, the AI can help the RE to enable the attainment of 42 out of 169 targets. With the current exponential growth of RE share and AI development together with addressing certain present limitations, this impact may cover additional targets in the future. Nevertheless, the present research foci neglect significant facets. The exponential growth of RE share and rapid evolution of AI need to be accompanied through the requisite regulatory insight and technology regulation to cover additional targets in the future.

On Sinofuturism

Screen Bodies ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. 46-62
Author(s):  
Yunying Huang
Keyword(s):  
Artificial Intelligence ◽  
Pop Culture ◽  
Chinese People ◽  
Modern Chinese ◽  
The Future ◽  
Dominant Design ◽  
Urban Rural ◽  
Cultural Expressions ◽  
Contemporary Chinese

Dominant design narratives about “the future” contain many contemporary manifestations of “orientalism” and Anti-Chineseness. In US discourse, Chinese people are often characterized as a single communist mass and the primary market for which this future is designed. By investigating the construction of modern Chinese pop culture in Chinese internet and artificial intelligence, and discussing different cultural expressions across urban, rural, and queer Chinese settings, I challenge external Eurocentric and orientalist perceptions of techno-culture in China, positing instead a view of Sinofuturism centered within contemporary Chinese contexts.

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