Incremental Learning Versus Batch Learning for Classification of User’s Behaviour in Medical Imaging

Carlos Viana-Ferreira, Sérgio Matos, Carlos Costa


Communication latency still hinders the adoption of Cloud computing paradigms in medical imaging environments where it could serve as a reliable technology to support repository outsourcing solutions or inter-institutional workflows, for instance. One way to overcome this is by implementing cache repositories and prefetching mechanisms. Nevertheless, such solutions are usually based on static rules that may inefficiently manage the cache storage capacity. For that reason, this paper compares a pattern recognition system using incremental learning versus batch learning, in order to assess which one could be more appropriately used in a medical imaging cache mechanism.


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Paper Citation

in Harvard Style

Viana-Ferreira C., Matos S. and Costa C. (2015). Incremental Learning Versus Batch Learning for Classification of User’s Behaviour in Medical Imaging . In Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015) ISBN 978-989-758-068-0, pages 431-438. DOI: 10.5220/0005219704310438

in Bibtex Style

author={Carlos Viana-Ferreira and Sérgio Matos and Carlos Costa},
title={Incremental Learning Versus Batch Learning for Classification of User’s Behaviour in Medical Imaging},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015)},

in EndNote Style

JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2015)
TI - Incremental Learning Versus Batch Learning for Classification of User’s Behaviour in Medical Imaging
SN - 978-989-758-068-0
AU - Viana-Ferreira C.
AU - Matos S.
AU - Costa C.
PY - 2015
SP - 431
EP - 438
DO - 10.5220/0005219704310438