Application of deep learning in cardiovascular medicine using multiple biomedical data

Giovanah Gogi; Alexander Gegov; Mohamed Bader-El-Den; Boriana Vatchova

doi:10.1109/IS48319.2020.9199844

Application of deep learning in cardiovascular medicine using multiple biomedical data

Giovanah Gogi
, Alexander Gegov
, Mohamed Bader-El-Den
, Boriana Vatchova

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

218 Downloads (Pure)

Abstract

Today with the help of emerging technologies scientists can gather data in many sectors which includes the Healthcare sector. The amount of data generated by machines and humans is overwhelming and is growing faster than it has ever had before. Taking advantage of all the power that exist in that data we have come up with a novel idea where we have used the development of machine learning techniques in diagnosing cardiovascular disease. Here, we fit a function to examples and using the function to generalize and make predictions about new diagnosis. In other words, the machine learning models learn from past data to make predictions about a patient diagnosis. This research provides a detailed work with the application of planning techniques is used in order to diagnose CVDs. A combination of biological data and medical imaging has been used. Ultimately, as this is a challenging research area open issues and its possible future works have also been discussed.

Original language	English
Title of host publication	2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings
Editors	Vassil Sgurev, Vladimir Jotsov, Rudolf Kruse, Mincho Hadjiski
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	200-204
Number of pages	5
ISBN (Electronic)	978-1-7281-5456-5
ISBN (Print)	978-1-7281-5457-2
DOIs	https://doi.org/10.1109/IS48319.2020.9199844
Publication status	Published - 18 Sept 2020
Event	10th IEEE International Conference on Intelligent Systems - Sofia, Bulgaria Duration: 28 Aug 2020 → 30 Aug 2020

Publication series

Name	2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings
Publisher	IEEE
ISSN (Print)	1541-1672

Conference

Conference	10th IEEE International Conference on Intelligent Systems
Abbreviated title	IS 2020
Country/Territory	Bulgaria
City	Sofia
Period	28/08/20 → 30/08/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

cardiovascular diseases
convolutional neural network
deep learning
U-Net

Access to Document

10.1109/IS48319.2020.9199844

IEEE paper Giovanah Gogi (1)
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Accepted author manuscript (Post-print), 312 KB

Cite this

Gogi, G., Gegov, A., Bader-El-Den, M., & Vatchova, B. (2020). Application of deep learning in cardiovascular medicine using multiple biomedical data. In V. Sgurev, V. Jotsov, R. Kruse, & M. Hadjiski (Eds.), 2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings (pp. 200-204). Article 9199844 (2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IS48319.2020.9199844

Gogi, Giovanah ; Gegov, Alexander ; Bader-El-Den, Mohamed et al. / Application of deep learning in cardiovascular medicine using multiple biomedical data. 2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings. editor / Vassil Sgurev ; Vladimir Jotsov ; Rudolf Kruse ; Mincho Hadjiski. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 200-204 (2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings).

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title = "Application of deep learning in cardiovascular medicine using multiple biomedical data",

abstract = "Today with the help of emerging technologies scientists can gather data in many sectors which includes the Healthcare sector. The amount of data generated by machines and humans is overwhelming and is growing faster than it has ever had before. Taking advantage of all the power that exist in that data we have come up with a novel idea where we have used the development of machine learning techniques in diagnosing cardiovascular disease. Here, we fit a function to examples and using the function to generalize and make predictions about new diagnosis. In other words, the machine learning models learn from past data to make predictions about a patient diagnosis. This research provides a detailed work with the application of planning techniques is used in order to diagnose CVDs. A combination of biological data and medical imaging has been used. Ultimately, as this is a challenging research area open issues and its possible future works have also been discussed.",

keywords = "cardiovascular diseases, convolutional neural network, deep learning, U-Net",

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Gogi, G, Gegov, A , Bader-El-Den, M & Vatchova, B 2020, Application of deep learning in cardiovascular medicine using multiple biomedical data. in V Sgurev, V Jotsov, R Kruse & M Hadjiski (eds), 2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings., 9199844, 2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 200-204, 10th IEEE International Conference on Intelligent Systems, Sofia, Bulgaria, 28/08/20. https://doi.org/10.1109/IS48319.2020.9199844

Application of deep learning in cardiovascular medicine using multiple biomedical data. / Gogi, Giovanah; Gegov, Alexander ; Bader-El-Den, Mohamed et al.
2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings. ed. / Vassil Sgurev; Vladimir Jotsov; Rudolf Kruse; Mincho Hadjiski. Institute of Electrical and Electronics Engineers Inc., 2020. p. 200-204 9199844 (2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Application of deep learning in cardiovascular medicine using multiple biomedical data

AU - Gogi, Giovanah

AU - Gegov, Alexander

AU - Bader-El-Den, Mohamed

AU - Vatchova, Boriana

PY - 2020/9/18

Y1 - 2020/9/18

N2 - Today with the help of emerging technologies scientists can gather data in many sectors which includes the Healthcare sector. The amount of data generated by machines and humans is overwhelming and is growing faster than it has ever had before. Taking advantage of all the power that exist in that data we have come up with a novel idea where we have used the development of machine learning techniques in diagnosing cardiovascular disease. Here, we fit a function to examples and using the function to generalize and make predictions about new diagnosis. In other words, the machine learning models learn from past data to make predictions about a patient diagnosis. This research provides a detailed work with the application of planning techniques is used in order to diagnose CVDs. A combination of biological data and medical imaging has been used. Ultimately, as this is a challenging research area open issues and its possible future works have also been discussed.

AB - Today with the help of emerging technologies scientists can gather data in many sectors which includes the Healthcare sector. The amount of data generated by machines and humans is overwhelming and is growing faster than it has ever had before. Taking advantage of all the power that exist in that data we have come up with a novel idea where we have used the development of machine learning techniques in diagnosing cardiovascular disease. Here, we fit a function to examples and using the function to generalize and make predictions about new diagnosis. In other words, the machine learning models learn from past data to make predictions about a patient diagnosis. This research provides a detailed work with the application of planning techniques is used in order to diagnose CVDs. A combination of biological data and medical imaging has been used. Ultimately, as this is a challenging research area open issues and its possible future works have also been discussed.

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PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 28 August 2020 through 30 August 2020

ER -

Gogi G, Gegov A , Bader-El-Den M, Vatchova B. Application of deep learning in cardiovascular medicine using multiple biomedical data. In Sgurev V, Jotsov V, Kruse R, Hadjiski M, editors, 2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. p. 200-204. 9199844. (2020 IEEE 10th International Conference on Intelligent Systems, IS 2020 - Proceedings). doi: 10.1109/IS48319.2020.9199844

Application of deep learning in cardiovascular medicine using multiple biomedical data

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this