Artificial Intelligence and Machine Learning

Artificial Intelligence and Machine Learning

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Home Gateways Artificial Intelligence and Machine Learning About
About this Gateway
The Artificial Intelligence and Machine Learning Gateway aims to provide stakeholders across academia, industry and policy with a space to disseminate work related to all areas of machine learning and AI research. By providing fast, open publication alongside access to underlying data the Gateway looks to facilitate the rapid and transparent sharing of research on the fundamentals and applications of Artificial Intelligence and machine learning. This research includes a broad range of topics and interdisciplinary areas such as applications of machine learning in other disciplines, deep learning, neural networks, smart technology, Internet of Things and cyber security, among others. 
 
The Gateway welcomes all articles relating to the areas listed above, as well as cross-disciplinary research relating to these important topics. To submit to the Gateway simply click the “Submit to this Gateway” button above or select the Gateway from dropdown list in the article submission form. 

Please also consider submitting to one of our linked Collections: For recipients of Horizon grant funding, please see our related Collections on Open Research Europe: If you would like to propose a themed Collection in a subject related to the Gateway or otherwise have any questions, please get in contact with us via research@f1000.com 
Gateway Areas
Fundamentals in AI and Machine Learning
This area focuses on recent breakthroughs, important advancements, and research findings in the domains of artificial intelligence and machine learning, including deep learning and other data-driven areas. This includes neural networks, deep learning, intelligent machines, machine learning models and AI development, and similar.
AI in Medicine and Healthcare
This area focuses on the transdisciplinary domain of AI applied to medicine and healthcare and aims to further leverage the potential of ‘big data’ routinely generated in life science and healthcare by tailoring it with cutting-edge advancement in AI and Machine Learning. Focusing on both technical and medical perspectives, this Gateway will include the development of new personalized medicine, drug and biomarker discoveries, preventative strategies, the design of impactful clinical trials, health informatics and digital healthcare, among others.
AI in Manufacturing, Materials and Smart Cities
This area aims to utilize the functionality and forward-thinking nature of AI and Machine Learning in order to improve engineering processes, such as design and manufacturing and the construction of smart cities. It includes, but not limited to, smart manufacturing and the reduction in faults, process improvements, AI in materials development, the use of Digital Twin technology to improve part matching, and the response of smart cities to user needs.
AI in Humanities and Social Sciences
This area focuses on the use of AI across the social sciences and humanities, and the impact of AI in these disciplines. This includes, but is not limited to, the use of machine learning and AI in psychological and behavioral studies, in cultural heritage projects, in music and sound design and technology, and in studies seeking to understand human movement and migration, as well as cultural, racial and gender biases in AI, social fears about AI and Machine Learning technology, and studies on the perception of AI in communities.
AI and Cybersecurity
Cybersecurity is one of the biggest concerns of modern societies - for governments, companies and individuals. At the forefront of technological developments, AI and Machine Learning is one of the most important areas for ensuring the transfer and storage of safe data across a wide range of internet applications. This includes AI for security measures, protecting sensitive information, prevention of malicious software and similar. 
Gateway Advisors

  • Parag Chatterjee
    National Technological University, Argentina & University of the Republic, Uruguay

  • Sally Ellingson
    University of Kentucky, USA

  • Hashem Koohy
    Oxford University, UK

  • Nagender Aneja
    School of Digital Science, Universiti Brunei Darussalam, Brunei

  • Gustavo Ramirez-Gonzalez
    Universidad del Cauca, Colombia

  • Andry Alamsyah
    Telkom University, Indonesia

  • Naveen Palanichamy
    Multimedia University, Malaysia

  • J Indumathi
    Anna University, Chennai, India

  • Oliver Bown
    University of New South Wales, Australia

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