@inproceedings{29f6a066d28142efaede5546091633c6,
title = "Proposing the deep dynamic Bayesian network as a future computer based medical system",
abstract = "The development of new learning models has been of great importance throughout recent years, with a focus on creating advances in the area of deep learning. Deep learning was first noted in 2006, and has since become a major area of research in a number of disciplines. This paper will delve into the area of deep learning to present its current limitations and provide a new idea for a fully integrated deep and dynamic probabilistic system. The new model will be applicable to a vast number of areas initially focusing on applications into medical image analysis with an overall goal of utilising this approach for prediction purposes in computer based medical systems.",
keywords = "Deep learning, Dynamic Bayesian network, Medical systems, Probabilistic graphical model",
author = "Carbery, {Caoimhe M.} and Marshall, {Adele H.} and Roger Woods",
year = "2016",
month = aug,
day = "18",
doi = "10.1109/CBMS.2016.70",
language = "English",
series = "IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "227--228",
booktitle = "Proceedings - IEEE 29th International Symposium on Computer-Based Medical Systems, CBMS 2016",
note = "29th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2016 ; Conference date: 20-06-2016 Through 23-06-2016",
}