About the symposium 

The focus of this 2-day symposium will be to bring together researchers and medical practitioners to discuss and share advances in the applications of artificial intelligence and machine learning to medical practice and research. This symposium will provide a catalyst for interdisciplinary collaboration and dialog with the aim of knowledge sharing, research presentation, and agenda setting.

Call for Abstract Submission

Benefiting from a huge amount of data with multiple modalities in the big data era, the rapid evolution of artificial intelligence (AI) is contributing to advances in medical applications. Such applications include genetic data are analysed for predicting risks of cancer or treatment outcome in oncology; clinical data from electronic health records are useful for predicting specific diseases, such as sepsis in intensive care units; and bio-signals can be processed by AI for many applications, such as electrocardiography. In particular, personalised medicine will benefit from intelligent, reliable, and responsible AI systems, therefore improving care and the quality of life.

Current machine learning systems often lack understanding of the relationship between causes and effects in their domain. Causal reasoning is, therefore, being recognized as a missing piece in AI methods. Integrating causality into machine learning methods will be integral for designing next generation intelligent systems. The causality framework allows researchers to represent medical background knowledge in an explainable manner. Thus, causal AI promises to improve further personalised medical applications with trustworthy and fair decision-making.

In this context, the AICPM Symposium is calling for high-quality abstract submissions in the research field of AI and medicine, with the goal of promoting research development and agenda setting in this interdisciplinary domain.

We invite discussions at the intersection of AI and outlined topics in medicine. The research topics include, but are not limited to:

• Specific uses and use cases of AI and ML in medical contexts, lessons learned and best practices 
• Reporting of specific data-intensive medical experiments  
• Prototypes of AI systems in medical applications, decision support systems 
• Machine learning approaches in medical applications 

The selected abstracts will be invited to be presented either in poster or oral format. There will also be an opportunity to submit full papers for publication in the Proceedings of the symposium. For submission we will follow the LNCS format. The overleaf link can be found  here. The latex and word templates can be downloaded  here.

Each submission is limited to a maximum of two pages. The abstracts can be submitted through EasyChair  here.