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

Christopher Neil Bull; Dommy Asfiandy; Ann Gledson; Joseph Mellor; Samuel Couth; Gemma Stringer; Paul Edward Rayson; Alistair Gordon Simpson Sutcliffe; John Keane; Xiao-Jun Zeng; Alistair Burns; Iracema Leroi; Clive Ballard; Peter Harvey Sawyer

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

Christopher Neil Bull, Dommy Asfiandy, Ann Gledson, Joseph Mellor, Samuel Couth, Gemma Stringer, Paul Edward Rayson, Alistair Gordon Simpson Sutcliffe, John Keane, Xiao-Jun Zeng, Alistair Burns, Iracema Leroi, Clive Ballard, Peter Harvey Sawyer

College of Engineering and Physical Sciences

Research output: Chapter in Book/Published conference output › Chapter

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?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.

Original language	English
Title of host publication	Resources and ProcessIng of linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric impairments (RaPID '16) workshop
Pages	35-40
Number of pages	6
Publication status	Published - 23 May 2016

Bibliographical note

Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

Keywords

Dementia
Corpus Linguistics
Natural Language Processing
Data Mining

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http://www.research.lancs.ac.uk/portal/en/publications/combining-data-mining-and-text-mining-for-detection-of-early-stage-dementia(9d834be1-7902-4ec2-9e72-82050f587f29).htmlLicence: CC BY-NC 3.0

Cite this

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 (pp. 35-40) http://www.research.lancs.ac.uk/portal/en/publications/combining-data-mining-and-text-mining-for-detection-of-early-stage-dementia(9d834be1-7902-4ec2-9e72-82050f587f29).html

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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?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}",

note = "Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License",

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",

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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. pp. 35-40. <http://www.research.lancs.ac.uk/portal/en/publications/combining-data-mining-and-text-mining-for-detection-of-early-stage-dementia(9d834be1-7902-4ec2-9e72-82050f587f29).html>

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. 2016. p. 35-40.

Research output: Chapter in Book/Published conference output › Chapter

TY - CHAP

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

N1 - Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

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

UR - http://www.lrec-conf.org/proceedings/lrec2016/workshops/LREC2016Workshop-RaPID2016_Proceedings.pdf

M3 - Chapter

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

ER -

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

Abstract

Bibliographical note

Keywords

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