Fuzzy logic in clinical practice decision support systems

Jim Warren; Gleb Beliakov; B.J. van der Zwaag

Fuzzy logic in clinical practice decision support systems

Jim Warren, Gleb Beliakov, B.J. van der Zwaag

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

35 Citations (Scopus)

161 Downloads (Pure)

Abstract

Computerized clinical guidelines can provide significant benefits to health outcomes and costs, however, their effective implementation presents significant problems. Vagueness and ambiguity inherent in natural (textual) clinical guidelines is not readily amenable to formulating automated alerts or advice. Fuzzy logic allows us to formalize the treatment of vagueness in a decision support architecture. This paper discusses sources of fuzziness in clinical practice guidelines. We consider how fuzzy logic can be applied and give a set of heuristics for the clinical guideline knowledge engineer for addressing uncertainty in practice guidelines. We describe the specific applicability of fuzzy logic to the decision support behavior of Care Plan On-Line, an intranet-based chronic care planning system for General Practitioners.

Original language	Undefined
Title of host publication	Proceedings of the 33rd Hawaii International Conference on Systems Sciences
Place of Publication	Maui, Hawaii
Publisher	IEEE
Pages	1-10
Number of pages	10
ISBN (Print)	0 7695 0493 0
Publication status	Published - Jan 2000
Event	33rd Hawaii International Conference on System Sciences, HICSS 2000 - Maui, United States Duration: 4 Jan 2000 → 7 Jan 2000 Conference number: 33

Publication series

Name
Publisher	IEEE Computer Society Press

Conference

Conference	33rd Hawaii International Conference on System Sciences, HICSS 2000
Abbreviated title	HICSS
Country/Territory	United States
City	Maui
Period	4/01/00 → 7/01/00

Keywords

EWI-1778
IR-17305
METIS-114200

Access to Document

http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=926789

Cite this

@inproceedings{055706ca0e66498c81e5395b4c3a5021,

title = "Fuzzy logic in clinical practice decision support systems",

abstract = "Computerized clinical guidelines can provide significant benefits to health outcomes and costs, however, their effective implementation presents significant problems. Vagueness and ambiguity inherent in natural (textual) clinical guidelines is not readily amenable to formulating automated alerts or advice. Fuzzy logic allows us to formalize the treatment of vagueness in a decision support architecture. This paper discusses sources of fuzziness in clinical practice guidelines. We consider how fuzzy logic can be applied and give a set of heuristics for the clinical guideline knowledge engineer for addressing uncertainty in practice guidelines. We describe the specific applicability of fuzzy logic to the decision support behavior of Care Plan On-Line, an intranet-based chronic care planning system for General Practitioners.",

keywords = "EWI-1778, IR-17305, METIS-114200",

author = "Jim Warren and Gleb Beliakov and \{van der Zwaag\}, B.J.",

year = "2000",

month = jan,

language = "Undefined",

isbn = "0 7695 0493 0",

publisher = "IEEE",

pages = "1--10",

booktitle = "Proceedings of the 33rd Hawaii International Conference on Systems Sciences",

address = "United States",

note = "33rd Hawaii International Conference on System Sciences, HICSS 2000 ; Conference date: 04-01-2000 Through 07-01-2000",

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Warren, J, Beliakov, G & van der Zwaag, BJ 2000, Fuzzy logic in clinical practice decision support systems. in Proceedings of the 33rd Hawaii International Conference on Systems Sciences. IEEE, Maui, Hawaii, pp. 1-10, 33rd Hawaii International Conference on System Sciences, HICSS 2000, Maui, Hawaii, United States, 4/01/00. <http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=926789>

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T1 - Fuzzy logic in clinical practice decision support systems

AU - Warren, Jim

AU - Beliakov, Gleb

AU - van der Zwaag, B.J.

N1 - Conference code: 33

PY - 2000/1

Y1 - 2000/1

N2 - Computerized clinical guidelines can provide significant benefits to health outcomes and costs, however, their effective implementation presents significant problems. Vagueness and ambiguity inherent in natural (textual) clinical guidelines is not readily amenable to formulating automated alerts or advice. Fuzzy logic allows us to formalize the treatment of vagueness in a decision support architecture. This paper discusses sources of fuzziness in clinical practice guidelines. We consider how fuzzy logic can be applied and give a set of heuristics for the clinical guideline knowledge engineer for addressing uncertainty in practice guidelines. We describe the specific applicability of fuzzy logic to the decision support behavior of Care Plan On-Line, an intranet-based chronic care planning system for General Practitioners.

AB - Computerized clinical guidelines can provide significant benefits to health outcomes and costs, however, their effective implementation presents significant problems. Vagueness and ambiguity inherent in natural (textual) clinical guidelines is not readily amenable to formulating automated alerts or advice. Fuzzy logic allows us to formalize the treatment of vagueness in a decision support architecture. This paper discusses sources of fuzziness in clinical practice guidelines. We consider how fuzzy logic can be applied and give a set of heuristics for the clinical guideline knowledge engineer for addressing uncertainty in practice guidelines. We describe the specific applicability of fuzzy logic to the decision support behavior of Care Plan On-Line, an intranet-based chronic care planning system for General Practitioners.

KW - EWI-1778

KW - IR-17305

KW - METIS-114200

M3 - Conference contribution

SN - 0 7695 0493 0

SP - 1

EP - 10

BT - Proceedings of the 33rd Hawaii International Conference on Systems Sciences

PB - IEEE

CY - Maui, Hawaii

T2 - 33rd Hawaii International Conference on System Sciences, HICSS 2000

Y2 - 4 January 2000 through 7 January 2000

ER -