Discussing Anomalous Situations using Decision Trees; A Head Injury Case Study

A. McQuatt; Derek Henry Sleeman; P. J. D. Andrews; V. Corruble; P. A. Jones

Discussing Anomalous Situations using Decision Trees; A Head Injury Case Study

A. McQuatt, Derek Henry Sleeman, P. J. D. Andrews, V. Corruble, P. A. Jones

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Abstract

Objectives. Predicting the outcome of seriously ill patients is a challenging problem for clinicians.

Methods: One alternative to clinical trials is to analyse existing patient data in an attempt to predict the. several outcomes, and to suggest therapies. In this paper we use decision tree techniques to predict the outcome of head injury patients. The work is based on patient data from the Edinburgh Royal Infirmary which contains both background (demographic) data and temporal (Physiological) data.

Results. The focus of this paper is the discussion of The anomalous cases in the decision trees with the domain experts (the clinicians).

Conclusions: These analyses led to the detection of several situations where both the data analysis and patient data collection should be enhanced, which in turn should lead to improved patient care.

Original language	English
Pages (from-to)	373-379
Number of pages	6
Journal	Methods of Information in Medicine
Volume	40
Publication status	Published - Nov 2001

Keywords

anomalies
decision tree analysis
demographic data
traumatic brain injuries
temporal/physiological data

Cite this

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title = "Discussing Anomalous Situations using Decision Trees; A Head Injury Case Study",

abstract = "Objectives. Predicting the outcome of seriously ill patients is a challenging problem for clinicians.Methods: One alternative to clinical trials is to analyse existing patient data in an attempt to predict the. several outcomes, and to suggest therapies. In this paper we use decision tree techniques to predict the outcome of head injury patients. The work is based on patient data from the Edinburgh Royal Infirmary which contains both background (demographic) data and temporal (Physiological) data.Results. The focus of this paper is the discussion of The anomalous cases in the decision trees with the domain experts (the clinicians).Conclusions: These analyses led to the detection of several situations where both the data analysis and patient data collection should be enhanced, which in turn should lead to improved patient care.",

keywords = "anomalies, decision tree analysis, demographic data, traumatic brain injuries, temporal/physiological data",

author = "A. McQuatt and Sleeman, {Derek Henry} and Andrews, {P. J. D.} and V. Corruble and Jones, {P. A.}",

year = "2001",

month = nov,

language = "English",

volume = "40",

pages = "373--379",

journal = "Methods of Information in Medicine",

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T1 - Discussing Anomalous Situations using Decision Trees; A Head Injury Case Study

AU - McQuatt, A.

AU - Sleeman, Derek Henry

AU - Andrews, P. J. D.

AU - Corruble, V.

AU - Jones, P. A.

PY - 2001/11

Y1 - 2001/11

N2 - Objectives. Predicting the outcome of seriously ill patients is a challenging problem for clinicians.Methods: One alternative to clinical trials is to analyse existing patient data in an attempt to predict the. several outcomes, and to suggest therapies. In this paper we use decision tree techniques to predict the outcome of head injury patients. The work is based on patient data from the Edinburgh Royal Infirmary which contains both background (demographic) data and temporal (Physiological) data.Results. The focus of this paper is the discussion of The anomalous cases in the decision trees with the domain experts (the clinicians).Conclusions: These analyses led to the detection of several situations where both the data analysis and patient data collection should be enhanced, which in turn should lead to improved patient care.

AB - Objectives. Predicting the outcome of seriously ill patients is a challenging problem for clinicians.Methods: One alternative to clinical trials is to analyse existing patient data in an attempt to predict the. several outcomes, and to suggest therapies. In this paper we use decision tree techniques to predict the outcome of head injury patients. The work is based on patient data from the Edinburgh Royal Infirmary which contains both background (demographic) data and temporal (Physiological) data.Results. The focus of this paper is the discussion of The anomalous cases in the decision trees with the domain experts (the clinicians).Conclusions: These analyses led to the detection of several situations where both the data analysis and patient data collection should be enhanced, which in turn should lead to improved patient care.

KW - anomalies

KW - decision tree analysis

KW - demographic data

KW - traumatic brain injuries

KW - temporal/physiological data

M3 - Article

SN - 0026-1270

VL - 40

SP - 373

EP - 379

JO - Methods of Information in Medicine

JF - Methods of Information in Medicine

ER -

Discussing Anomalous Situations using Decision Trees; A Head Injury Case Study

Abstract

Keywords

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