Providing embedded proactive task support for diagnostic jobs: A neural network-based approach

Y. W. Leung; J. Y. Mao

doi:10.1016/S0957-4174(03)00051-4

Providing embedded proactive task support for diagnostic jobs: A neural network-based approach

Y. W. Leung
, J. Y. Mao

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

7 Citations (Scopus)

Abstract

This research proposes the use of a neural network (NN) to provide proactive task support, which is embedded in user's primary application for diagnostic jobs. What is unique about this research is that the NN serves as not only the backend inference engine, but also the driver of the user interface at the front-end. The user interface features separate and persistent advice windows, where procedural advice and relevant domain knowledge are displayed continuously, side-by-side to the task window. The display is updated at short intervals, according to the task progress. At the backend, the NN, complemented by a simple semantic network, makes inference about a user's task and continuously refines its inference. A prototype has been built to demonstrate the proposed approach. It supports novice nurses' triage task based on a telephone interview. The usability of the prototype has been informally evaluated at a medical call center and the feedback was largely positive. © 2003 Elsevier Science Ltd. All rights reserved.

Original language	English
Pages (from-to)	255-267
Journal	Expert Systems with Applications
Volume	25
Issue number	2
DOIs	https://doi.org/10.1016/S0957-4174(03)00051-4
Publication status	Published - Aug 2003
Externally published	Yes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

This research is funded by an operating grant to the second author from the Social Science and Humanities Research Council of Canada (SSHRC) when he was a faculty member at the University of Waterloo.

Research Keywords

Diagnostic tasks
Embedded task support
Neural networks for user interfaces
Proactive task support

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title = "Providing embedded proactive task support for diagnostic jobs: A neural network-based approach",

abstract = "This research proposes the use of a neural network (NN) to provide proactive task support, which is embedded in user's primary application for diagnostic jobs. What is unique about this research is that the NN serves as not only the backend inference engine, but also the driver of the user interface at the front-end. The user interface features separate and persistent advice windows, where procedural advice and relevant domain knowledge are displayed continuously, side-by-side to the task window. The display is updated at short intervals, according to the task progress. At the backend, the NN, complemented by a simple semantic network, makes inference about a user's task and continuously refines its inference. A prototype has been built to demonstrate the proposed approach. It supports novice nurses' triage task based on a telephone interview. The usability of the prototype has been informally evaluated at a medical call center and the feedback was largely positive. {\textcopyright} 2003 Elsevier Science Ltd. All rights reserved.",

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AU - Mao, J. Y.

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N2 - This research proposes the use of a neural network (NN) to provide proactive task support, which is embedded in user's primary application for diagnostic jobs. What is unique about this research is that the NN serves as not only the backend inference engine, but also the driver of the user interface at the front-end. The user interface features separate and persistent advice windows, where procedural advice and relevant domain knowledge are displayed continuously, side-by-side to the task window. The display is updated at short intervals, according to the task progress. At the backend, the NN, complemented by a simple semantic network, makes inference about a user's task and continuously refines its inference. A prototype has been built to demonstrate the proposed approach. It supports novice nurses' triage task based on a telephone interview. The usability of the prototype has been informally evaluated at a medical call center and the feedback was largely positive. © 2003 Elsevier Science Ltd. All rights reserved.

AB - This research proposes the use of a neural network (NN) to provide proactive task support, which is embedded in user's primary application for diagnostic jobs. What is unique about this research is that the NN serves as not only the backend inference engine, but also the driver of the user interface at the front-end. The user interface features separate and persistent advice windows, where procedural advice and relevant domain knowledge are displayed continuously, side-by-side to the task window. The display is updated at short intervals, according to the task progress. At the backend, the NN, complemented by a simple semantic network, makes inference about a user's task and continuously refines its inference. A prototype has been built to demonstrate the proposed approach. It supports novice nurses' triage task based on a telephone interview. The usability of the prototype has been informally evaluated at a medical call center and the feedback was largely positive. © 2003 Elsevier Science Ltd. All rights reserved.

KW - Diagnostic tasks

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KW - Neural networks for user interfaces

KW - Proactive task support

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DO - 10.1016/S0957-4174(03)00051-4

M3 - RGC 21 - Publication in refereed journal

SN - 0957-4174

VL - 25

SP - 255

EP - 267

JO - Expert Systems with Applications

JF - Expert Systems with Applications

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ER -

Providing embedded proactive task support for diagnostic jobs: A neural network-based approach

Abstract

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Research Keywords

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