-------- Forwarded Message -------- Subject: [WI] CfP: 5th International Workshop on Knowledge Discovery in Healthcare Data (@ECAI 2020) - papers due on Mar 6th Date: Thu, 9 Jan 2020 09:52:31 +0000 From: Kerstin Bach kerstin.bach@ntnu.no Reply-To: Kerstin Bach kerstin.bach@ntnu.no To: wi@lists.kit.edu wi@lists.kit.edu
Dear all,
The 5th International Workshop on Knowledge Discovery in Healthcare Data will be held during ECAI 2020 in Santiago de Compostela (Spain) on June 8 or 9, 2020.
Important Deadlines: • Technical Paper: March 6th, 2020 • BGLP Challenge: March 24th, 2020 There are many healthcare datasets consisting of both structured and unstructured information, which provide a challenge for artificial intelligence and machine learning researchers seeking to extract knowledge from data. Existing healthcare datasets include electronic medical records, large collections of complex physiological information, medical imaging data, genomics, as well as other socio-economic and behavioral data. In order to perform data-driven analysis or build causal and inferential models using these datasets, challenges such as integrating multiple data types, dealing with missing data, and handling irregularly sampled data need to be addressed. While these challenges must be considered by researchers working with healthcare data, a larger problem involves how to best ensure that the hypotheses posed and types of knowledge discoveries sought are relevant to the healthcare community. Clinical perspectives from medical professionals are required to ensure that advancements in healthcare data analysis result in positive impact to point-of-care and outcome-based systems.
This workshop builds upon the success of previous Knowledge Discovery in Healthcare Data (KDH) workshops. It welcomes contributions providing insight on the extent to which AI techniques have successfully penetrated the healthcare field, interaction among AI techniques to achieve successful learning healthcare systems, and distinctions between AI and non-AI models needed in modern healthcare environments. The focus of the workshop is on issues in data extraction and assembly, knowledge discovery, decision support for healthcare providers, and personalised self-care aids for patients. A workshop highlight will be the Blood Glucose Level Prediction (BGLP) Challenge, in which researchers will compare the efficacy of different machine learning prediction approaches on a standard set of data from patients with type 1 diabetes.
Main Topics: • Knowledge discovery and data analytics • Data extraction, organization and assembly • Personalisation and decision support • Blood glucose level prediction
A full list of topics and submission guidelines can be found at: https://sites.google.com/view/kdh-2020
Kerstin Bach, Cindy Marling, Nirmalie Wiratunga Workshop Organizers