AI4Health

The AI4Health community covers the whole range of theoretical and practical aspects, technologies, and systems related to the application of artificial intelligence to issues such as machine learning, deep learning, knowledge discovery, decision support, regression, forecasting, optimization, and feature selection in the healthcare and wellbeing domain.

Our motivation:

eHealth is one of the major research and educational topics that have been attracting cross-disciplinary students and research groups in Europe. The deployment of new emerging technologies for health, especially based on Artificial Intelligence, is attracting the interest of many different stakeholders.

Our goal:

Within our community, we aim at bringing together students and researchers from academia from all nine EELISA universities, as well as industry, government and medical centers in order to present the state of the art and discuss the latest advances in the emerging area of the use of Artificial Intelligence and Soft Computing techniques.

How to participate:

Creating multidisciplinary teams including stakeholders like medical doctors and computer scientist

• Contributing to personalized healthcare using AI
• Modelling of brain functions (human brain to model and implementation)
• Establishing cross-disciplinary collaborations (co-supervision, co-mentorship in EELISA)
• Organizing diversity-promoting summer schools and workshops
• Promoting geographic diversity and inclusiveness, supporting students in low and middle-income countries

Further information:

The topics of interest include but are not limited to, the application of artificial intelligence and soft computing methodologies to:

• Knowledge Management of Health Data
• Data Mining and Knowledge Discovery in Healthcare
• Machine and Deep Learning approaches for Health Data
• Explainable AI models for Health, Biology and Medicine
• Decision Support Systems for Healthcare and Wellbeing
• AI for Precision Medicine
• Optimization for Healthcare problems
• Regression and Forecasting for Medical and/or Biomedical Signals
• Healthcare Information Systems
• Wellness Information Systems
• Information and networking security in healthcare
• Medical Signal and Image Processing and Techniques
• Medical Expert Systems
• Biomedical Applications
• Diagnosis and Therapy Support Systems
• Applications of AI in Healthcare and Wellbeing Systems
• Machine Learning-based Medical Systems
• Medical Data and Knowledge Bases
• Neural Networks in Medicine
• Ambient Intelligence and Pervasive Computing in Medicine and Healthcare
• AI in genomics
• AI for Healthcare Social Networks
• Healthcare Devices and Circuits for Artificial Intelligence