Computer-based learning to improve breast cancer detection skills

Yan Chen; Alastair Gale; Hazel  Scott; Andrew Evans; Jonathan James

doi:10.1007/978-3-642-02583-9_6

Computer-based learning to improve breast cancer detection skills

Yan Chen, Alastair Gale, Hazel Scott, Andrew Evans, Jonathan James

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

3 Citations (Scopus)

Abstract

In breast cancer screening it is important both to improve and maintain cancer detection skills at their highest levels. The introduction of digital imaging enables computer-based learning to be undertaken outside breast screening centres using a range of different devices. The potential for providing computer-based interpretation training using low-cost devices is detailed. The results demonstrated that naive observers can be trained to recognise certain key breast cancer appearances using a low cost display monitor along with a range of HCI techniques.

Original language	English
Title of host publication	Human-Computer Interaction. Interacting in Various Application Domains
Subtitle of host publication	13th International Conference, HCI International 2009, San Diego, CA, USA, July 19-24, 2009, Proceedings, Part IV
Editors	Julie A. Jacko
Place of Publication	Berlin
Publisher	Springer
Pages	49-57
Number of pages	9
ISBN (Electronic)	978642025839
ISBN (Print)	9783642025822
DOIs	https://doi.org/10.1007/978-3-642-02583-9_6
Publication status	Published - 2009
Event	13th International Conference on Human-Computer Interaction - San Diego, United States Duration: 19 Jul 2009 → 24 Jul 2009 http://www.hci.international/index.php?module=conference&CF_op=view&CF_id=21

Publication series

Name	Lecture notes in computer science
Publisher	Springer
Volume	5613
ISSN (Print)	0302-9743

Conference

Conference	13th International Conference on Human-Computer Interaction
Abbreviated title	HCI International 2009
Country/Territory	United States
City	San Diego
Period	19/07/09 → 24/07/09
Internet address	http://www.hci.international/index.php?module=conference&CF_op=view&CF_id=21

UN SDGs

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

Access to Document

10.1007/978-3-642-02583-9_6

Cite this

Chen, Y., Gale, A., Scott, H., Evans, A., & James, J. (2009). Computer-based learning to improve breast cancer detection skills. In J. A. Jacko (Ed.), Human-Computer Interaction. Interacting in Various Application Domains: 13th International Conference, HCI International 2009, San Diego, CA, USA, July 19-24, 2009, Proceedings, Part IV (pp. 49-57). (Lecture notes in computer science; Vol. 5613). Springer . https://doi.org/10.1007/978-3-642-02583-9_6

Chen, Yan ; Gale, Alastair ; Scott, Hazel et al. / Computer-based learning to improve breast cancer detection skills. Human-Computer Interaction. Interacting in Various Application Domains: 13th International Conference, HCI International 2009, San Diego, CA, USA, July 19-24, 2009, Proceedings, Part IV. editor / Julie A. Jacko. Berlin : Springer , 2009. pp. 49-57 (Lecture notes in computer science).

@inproceedings{27d0c7b187fe4b96a533f16333199f62,

title = "Computer-based learning to improve breast cancer detection skills",

abstract = "In breast cancer screening it is important both to improve and maintain cancer detection skills at their highest levels. The introduction of digital imaging enables computer-based learning to be undertaken outside breast screening centres using a range of different devices. The potential for providing computer-based interpretation training using low-cost devices is detailed. The results demonstrated that naive observers can be trained to recognise certain key breast cancer appearances using a low cost display monitor along with a range of HCI techniques.",

author = "Yan Chen and Alastair Gale and Hazel Scott and Andrew Evans and Jonathan James",

year = "2009",

doi = "10.1007/978-3-642-02583-9\_6",

language = "English",

isbn = "9783642025822",

series = "Lecture notes in computer science",

publisher = "Springer ",

pages = "49--57",

editor = "Jacko, \{Julie A.\}",

booktitle = "Human-Computer Interaction. Interacting in Various Application Domains",

note = "13th International Conference on Human-Computer Interaction, HCI International 2009 ; Conference date: 19-07-2009 Through 24-07-2009",

url = "http://www.hci.international/index.php?module=conference\&CF\_op=view\&CF\_id=21",

}

Chen, Y, Gale, A, Scott, H, Evans, A & James, J 2009, Computer-based learning to improve breast cancer detection skills. in JA Jacko (ed.), Human-Computer Interaction. Interacting in Various Application Domains: 13th International Conference, HCI International 2009, San Diego, CA, USA, July 19-24, 2009, Proceedings, Part IV. Lecture notes in computer science, vol. 5613, Springer , Berlin, pp. 49-57, 13th International Conference on Human-Computer Interaction, San Diego, United States, 19/07/09. https://doi.org/10.1007/978-3-642-02583-9_6

Computer-based learning to improve breast cancer detection skills. / Chen, Yan; Gale, Alastair; Scott, Hazel et al.
Human-Computer Interaction. Interacting in Various Application Domains: 13th International Conference, HCI International 2009, San Diego, CA, USA, July 19-24, 2009, Proceedings, Part IV. ed. / Julie A. Jacko. Berlin: Springer , 2009. p. 49-57 (Lecture notes in computer science; Vol. 5613).

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

TY - GEN

T1 - Computer-based learning to improve breast cancer detection skills

AU - Chen, Yan

AU - Gale, Alastair

AU - Scott, Hazel

AU - Evans, Andrew

AU - James, Jonathan

PY - 2009

Y1 - 2009

N2 - In breast cancer screening it is important both to improve and maintain cancer detection skills at their highest levels. The introduction of digital imaging enables computer-based learning to be undertaken outside breast screening centres using a range of different devices. The potential for providing computer-based interpretation training using low-cost devices is detailed. The results demonstrated that naive observers can be trained to recognise certain key breast cancer appearances using a low cost display monitor along with a range of HCI techniques.

AB - In breast cancer screening it is important both to improve and maintain cancer detection skills at their highest levels. The introduction of digital imaging enables computer-based learning to be undertaken outside breast screening centres using a range of different devices. The potential for providing computer-based interpretation training using low-cost devices is detailed. The results demonstrated that naive observers can be trained to recognise certain key breast cancer appearances using a low cost display monitor along with a range of HCI techniques.

UR - https://www.scopus.com/pages/publications/70349129010

U2 - 10.1007/978-3-642-02583-9_6

DO - 10.1007/978-3-642-02583-9_6

M3 - Conference contribution

AN - SCOPUS:70349129010

SN - 9783642025822

T3 - Lecture notes in computer science

SP - 49

EP - 57

BT - Human-Computer Interaction. Interacting in Various Application Domains

A2 - Jacko, Julie A.

PB - Springer

CY - Berlin

T2 - 13th International Conference on Human-Computer Interaction

Y2 - 19 July 2009 through 24 July 2009

ER -

Chen Y, Gale A, Scott H, Evans A, James J. Computer-based learning to improve breast cancer detection skills. In Jacko JA, editor, Human-Computer Interaction. Interacting in Various Application Domains: 13th International Conference, HCI International 2009, San Diego, CA, USA, July 19-24, 2009, Proceedings, Part IV. Berlin: Springer . 2009. p. 49-57. (Lecture notes in computer science). doi: 10.1007/978-3-642-02583-9_6

Computer-based learning to improve breast cancer detection skills

Abstract

Publication series

Conference

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this