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Clinical features of dementia associated with apolipoprotein ε4: discrimination with a neural network genetic algorithm.

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Title: Clinical features of dementia associated with apolipoprotein ε4: discrimination with a neural network genetic algorithm.
Authors: Jefferson, M. F., Burlinson, S., Burns, A., Mann, D., Pickering-Brown, S., Owen, F., Sriwardhana, C., Pendleton, N., Horan, M. A.
Source: International Journal of Geriatric Psychiatry. Jan2001, Vol. 16 Issue 1, p77-81. 5p. 1 Diagram, 3 Charts.
Subjects: Dementia, Alzheimer's disease, Genetic algorithms, Apolipoprotein E, Biological neural networks
Abstract: Background It is unclear whether the APOE ε4 allele is associated with distinct clinical features in dementia. Method 100 cases meeting ICD criteria for dementia were interviewed using standardized instruments and genotyped for APOE. The presence of the ε4 allele was used by a genetic algorithm neural network (GANN) to discriminate symptoms and signs. Results The GANN selected six features: gender, systolic blood pressure, absence of ankle tendon reflexes, history of weight loss, history of falls, and interviewer observed lability of mood. Using these features, a neural network discriminated cases according to ε4 highly accurately (area under receiver operating characteristic=0.83, sensitivity=0.78, specificity=0.78). Conclusions A GANN is able to discriminate a clinically distinct group of features among dementia patients who express the ε4 allele. Copyright © 2001 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Geriatric Psychiatry is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Clinical features of dementia associated with apolipoprotein ε4: discrimination with a neural network genetic algorithm.
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  Data: <searchLink fieldCode="AR" term="%22Jefferson%2C+M%2E+F%2E%22">Jefferson, M. F.</searchLink><br /><searchLink fieldCode="AR" term="%22Burlinson%2C+S%2E%22">Burlinson, S.</searchLink><br /><searchLink fieldCode="AR" term="%22Burns%2C+A%2E%22">Burns, A.</searchLink><br /><searchLink fieldCode="AR" term="%22Mann%2C+D%2E%22">Mann, D.</searchLink><br /><searchLink fieldCode="AR" term="%22Pickering-Brown%2C+S%2E%22">Pickering-Brown, S.</searchLink><br /><searchLink fieldCode="AR" term="%22Owen%2C+F%2E%22">Owen, F.</searchLink><br /><searchLink fieldCode="AR" term="%22Sriwardhana%2C+C%2E%22">Sriwardhana, C.</searchLink><br /><searchLink fieldCode="AR" term="%22Pendleton%2C+N%2E%22">Pendleton, N.</searchLink><br /><searchLink fieldCode="AR" term="%22Horan%2C+M%2E+A%2E%22">Horan, M. A.</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Geriatric+Psychiatry%22">International Journal of Geriatric Psychiatry</searchLink>. Jan2001, Vol. 16 Issue 1, p77-81. 5p. 1 Diagram, 3 Charts.
– Name: Subject
  Label: Subjects
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  Data: <searchLink fieldCode="DE" term="%22Dementia%22">Dementia</searchLink><br /><searchLink fieldCode="DE" term="%22Alzheimer's+disease%22">Alzheimer's disease</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Apolipoprotein+E%22">Apolipoprotein E</searchLink><br /><searchLink fieldCode="DE" term="%22Biological+neural+networks%22">Biological neural networks</searchLink>
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  Data: Background It is unclear whether the APOE ε4 allele is associated with distinct clinical features in dementia. Method 100 cases meeting ICD criteria for dementia were interviewed using standardized instruments and genotyped for APOE. The presence of the ε4 allele was used by a genetic algorithm neural network (GANN) to discriminate symptoms and signs. Results The GANN selected six features: gender, systolic blood pressure, absence of ankle tendon reflexes, history of weight loss, history of falls, and interviewer observed lability of mood. Using these features, a neural network discriminated cases according to ε4 highly accurately (area under receiver operating characteristic=0.83, sensitivity=0.78, specificity=0.78). Conclusions A GANN is able to discriminate a clinically distinct group of features among dementia patients who express the ε4 allele. Copyright © 2001 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Geriatric Psychiatry is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Genetic algorithms
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      – SubjectFull: Apolipoprotein E
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      – SubjectFull: Biological neural networks
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              Text: Jan2001
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