Identification of promising research directions using machine learning aided medical literature analysis

Victor Andrei; Ognjen Arandjelovic

doi:10.1109/EMBC.2016.7591231

Identification of promising research directions using machine learning aided medical literature analysis

Victor Andrei, Ognjen Arandjelovic

School of Computer Science

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

Abstract

The rapidly expanding corpus of medical research literature presents major challenges in the understanding of previous work, the extraction of maximum information from collected data, and the identification of promising research directions. We present a case for the use of advanced machine learning techniques as an aide in this task and introduce a novel methodology that is shown to be capable of extracting meaningful information from large longitudinal corpora, and of tracking complex temporal changes within it.

Original language	English
Title of host publication	2016 IEEE 38th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC)
Publisher	IEEE
Pages	2471-2474
ISBN (Electronic)	9781457702204
DOIs	https://doi.org/10.1109/EMBC.2016.7591231
Publication status	Published - 16 Aug 2016
Event	38th International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Disney's Contemporary Resort, Orlando, United States Duration: 16 Aug 2016 → 20 Aug 2016 Conference number: 38 http://embc.embs.org/2016/

Conference

Conference	38th International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Abbreviated title	EMBC
Country/Territory	United States
City	Orlando
Period	16/08/16 → 20/08/16
Internet address	http://embc.embs.org/2016/

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10.1109/EMBC.2016.7591231

Andrei_Identification_EMBC2016_AAM
© 2016, IEEE. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at ieeexplore.ieee.org / https://doi.org/10.1109/EMBC.2016.7591231
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title = "Identification of promising research directions using machine learning aided medical literature analysis",

abstract = "The rapidly expanding corpus of medical research literature presents major challenges in the understanding of previous work, the extraction of maximum information from collected data, and the identification of promising research directions. We present a case for the use of advanced machine learning techniques as an aide in this task and introduce a novel methodology that is shown to be capable of extracting meaningful information from large longitudinal corpora, and of tracking complex temporal changes within it.",

author = "Victor Andrei and Ognjen Arandjelovic",

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booktitle = "2016 IEEE 38th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC)",

publisher = "IEEE",

note = "38th International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016, EMBC ; Conference date: 16-08-2016 Through 20-08-2016",

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Andrei, V & Arandjelovic, O 2016, Identification of promising research directions using machine learning aided medical literature analysis. in 2016 IEEE 38th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC)., 7591231, IEEE, pp. 2471-2474, 38th International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016, Orlando, United States, 16/08/16. https://doi.org/10.1109/EMBC.2016.7591231

Identification of promising research directions using machine learning aided medical literature analysis. / Andrei, Victor; Arandjelovic, Ognjen.
2016 IEEE 38th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC). IEEE, 2016. p. 2471-2474 7591231.

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

TY - GEN

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T2 - 38th International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016

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Identification of promising research directions using machine learning aided medical literature analysis

Abstract

Conference

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