Challenges and roadmap for machine learning from medical data streams

Learning from Medical Data Streams 2011.

医药卫生;计算机科学

Experts Panel Summary

Others  :  http://ceur-ws.org/Vol-765/paper8.pdf
PID  :  41143

来源: CEUR

【 摘 要 】

Given that it is still a young research area, the workshopaimed at convening researchers from related elds in order to nd and consolidate a network of interests. To that extent, the workshop pro- moted a panel discussion on the \Challenges and roadmap for machine learning from medical data streams", with the participation of three scholar experts: Carlo Combi (University of Verona, Italy), an expert on temporal information systems, with an emphasis on the management of clinical information; Carolyn McGregor (University of Ontario Insti- tute of Technology, Canada), an expert on health informatics, with an emphasis on data streams processing in critical care settings; and Jo~ao Gama (University of Porto, Portugal), an expert on machine learning, with an emphasis on learning from ubiquitous data streams. Several top- ics were suggested to be discussed, such as the main domains where medical data is produced as a stream, and issues that dierentiate this research area from other related elds. Overall, most experts opinion fo- cused on the need to address problems on a temporal basis: temporal processing of data, temporal modelling of the reality, temporal learning from data, and temporal assessment of knowledge. Globally, the panel