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Combining data mining and text mining for detection of early stage dementia: the SAMS framework

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Combining data mining and text mining for detection of early stage dementia: the SAMS framework. / Bull, Christopher Neil; Asfiandy, Dommy; Gledson, Ann et al.
Resources and ProcessIng of linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric impairments (RaPID '16) workshop: Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC '16). European Language Resources Association (ELRA), 2016. p. 35-40.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Bull, CN, Asfiandy, D, Gledson, A, Mellor, J, Couth, S, Stringer, G, Rayson, PE, Sutcliffe, AGS, Keane, J, Zeng, X-J, Burns, A, Leroi, I, Ballard, C & Sawyer, PH 2016, Combining data mining and text mining for detection of early stage dementia: the SAMS framework. in Resources and ProcessIng of linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric impairments (RaPID '16) workshop: Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC '16). European Language Resources Association (ELRA), pp. 35-40. <http://www.lrec-conf.org/proceedings/lrec2016/workshops/LREC2016Workshop-RaPID2016_Proceedings.pdf>

APA

Bull, C. N., Asfiandy, D., Gledson, A., Mellor, J., Couth, S., Stringer, G., Rayson, P. E., Sutcliffe, A. G. S., Keane, J., Zeng, X-J., Burns, A., Leroi, I., Ballard, C., & Sawyer, P. H. (2016). Combining data mining and text mining for detection of early stage dementia: the SAMS framework. In Resources and ProcessIng of linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric impairments (RaPID '16) workshop: Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC '16) (pp. 35-40). European Language Resources Association (ELRA). http://www.lrec-conf.org/proceedings/lrec2016/workshops/LREC2016Workshop-RaPID2016_Proceedings.pdf

Vancouver

Bull CN, Asfiandy D, Gledson A, Mellor J, Couth S, Stringer G et al. Combining data mining and text mining for detection of early stage dementia: the SAMS framework. In Resources and ProcessIng of linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric impairments (RaPID '16) workshop: Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC '16). European Language Resources Association (ELRA). 2016. p. 35-40

Author

Bull, Christopher Neil ; Asfiandy, Dommy ; Gledson, Ann et al. / Combining data mining and text mining for detection of early stage dementia : the SAMS framework. Resources and ProcessIng of linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric impairments (RaPID '16) workshop: Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC '16). European Language Resources Association (ELRA), 2016. pp. 35-40

Bibtex

@inproceedings{9d834be179024ec29e7282050f587f29,
title = "Combining data mining and text mining for detection of early stage dementia: the SAMS framework",
abstract = "In this paper, we describe the open-source SAMS framework whose novelty lies in bringing together both data collection (keystrokes, mouse movements, application pathways) and text collection (email, documents, diaries) and analysis methodologies. The aim of SAMS is to provide a non-invasive method for large scale collection, secure storage, retrieval and analysis of an individual{\textquoteright}s computer usage for the detection of cognitive decline, and to infer whether this decline is consistent with the early stages of dementia. The framework will allow evaluation and study by medical professionals in which data and textual features can be linked to deficits in cognitive domains that are characteristic of dementia. Having described requirements gathering and ethical concerns in previous papers, here we focus on the implementation of the data and text collection components.",
keywords = "Dementia, Corpus Linguistics, Natural Language Processing, Data Mining",
author = "Bull, {Christopher Neil} and Dommy Asfiandy and Ann Gledson and Joseph Mellor and Samuel Couth and Gemma Stringer and Rayson, {Paul Edward} and Sutcliffe, {Alistair Gordon Simpson} and John Keane and Xiao-Jun Zeng and Alistair Burns and Iracema Leroi and Clive Ballard and Sawyer, {Peter Harvey}",
year = "2016",
month = may,
day = "23",
language = "English",
pages = "35--40",
booktitle = "Resources and ProcessIng of linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric impairments (RaPID '16) workshop",
publisher = "European Language Resources Association (ELRA)",

}

RIS

TY - GEN

T1 - Combining data mining and text mining for detection of early stage dementia

T2 - the SAMS framework

AU - Bull, Christopher Neil

AU - Asfiandy, Dommy

AU - Gledson, Ann

AU - Mellor, Joseph

AU - Couth, Samuel

AU - Stringer, Gemma

AU - Rayson, Paul Edward

AU - Sutcliffe, Alistair Gordon Simpson

AU - Keane, John

AU - Zeng, Xiao-Jun

AU - Burns, Alistair

AU - Leroi, Iracema

AU - Ballard, Clive

AU - Sawyer, Peter Harvey

PY - 2016/5/23

Y1 - 2016/5/23

N2 - In this paper, we describe the open-source SAMS framework whose novelty lies in bringing together both data collection (keystrokes, mouse movements, application pathways) and text collection (email, documents, diaries) and analysis methodologies. The aim of SAMS is to provide a non-invasive method for large scale collection, secure storage, retrieval and analysis of an individual’s computer usage for the detection of cognitive decline, and to infer whether this decline is consistent with the early stages of dementia. The framework will allow evaluation and study by medical professionals in which data and textual features can be linked to deficits in cognitive domains that are characteristic of dementia. Having described requirements gathering and ethical concerns in previous papers, here we focus on the implementation of the data and text collection components.

AB - In this paper, we describe the open-source SAMS framework whose novelty lies in bringing together both data collection (keystrokes, mouse movements, application pathways) and text collection (email, documents, diaries) and analysis methodologies. The aim of SAMS is to provide a non-invasive method for large scale collection, secure storage, retrieval and analysis of an individual’s computer usage for the detection of cognitive decline, and to infer whether this decline is consistent with the early stages of dementia. The framework will allow evaluation and study by medical professionals in which data and textual features can be linked to deficits in cognitive domains that are characteristic of dementia. Having described requirements gathering and ethical concerns in previous papers, here we focus on the implementation of the data and text collection components.

KW - Dementia

KW - Corpus Linguistics

KW - Natural Language Processing

KW - Data Mining

M3 - Conference contribution/Paper

SP - 35

EP - 40

BT - Resources and ProcessIng of linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric impairments (RaPID '16) workshop

PB - European Language Resources Association (ELRA)

ER -