| Authors | P. Halvorsen, M. Riegler and K. Schoeffmann |
| Editors | L. Amsaleg, B. Huet, M. Larson, G. Gravier, H. Hung, C. Ngo and W. T. Ooi |
| Title | Medical Multimedia Systems and Applications |
| Afilliation | Machine Learning |
| Project(s) | Department of Holistic Systems |
| Status | Published |
| Publication Type | Proceedings, refereed |
| Year of Publication | 2019 |
| Conference Name | Proceedings of the 27th ACM International Conference on Multimedia - MM '19 |
| Pagination | 2711-2713 |
| Date Published | 1072019 |
| Publisher | ACM Press |
| Place Published | New York, NY, USA |
| ISBN Number | 9781450368896 |
| Abstract | In recent years, we have observed a rise of interest in the multimedia community towards research topics related to health. It can be observed that this goes into two interesting directions. One is personal health with a larger focus on well-being and everyday healthy living. The other direction focuses more on multimedia challenges within the health-care systems, for example, how can multimedia content produced in hospitals be used efficiently but also on the user perspective of patients and health-care personal. Challenges and requirements in this interesting and challenging direction are similar to classic multimedia research, but with some additional pitfalls and challenges. This tutorial aims to give a general introduction to the research area; to provide an overview of specific requirements, pitfalls and challenges; to discuss existing and possible future work; and to elaborate on how machine learning approaches can help in multimedia-related challenges to improve the health-care quality for patients and support medical experts in their daily work. |
| URL | http://dl.acm.org/citation.cfm?doid=3343031http://dl.acm.org/citation.cfm?doid=3343031.3351319http://dl.acm.org/ft_gateway.cfm?id=3351319&ftid=2091902&dwn=1 |
| DOI | 10.1145/3343031.3351319 |
| Citation Key | 26859 |

