A Case-Based Reasoning system for complex medical diagnosis.
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| Title: | A Case-Based Reasoning system for complex medical diagnosis. |
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| Authors: | Chattopadhyay, Subhagata1 subhagatachatterjee@yahoo.com, Banerjee, Suvendu2 suvendu_banerjee@yahoo.com, Rabhi, Fethi A.3 f.rabhi@unsw.edu.au, Acharya, U. Rajendra4 aru@np.edu.sg |
| Source: | Expert Systems. Feb2013, Vol. 30 Issue 1, p12-20. 9p. 1 Color Photograph, 3 Diagrams, 3 Charts, 1 Graph. |
| Subjects: | Case-based reasoning, Computer diagnostic software, Premenstrual syndrome, Information retrieval, Gynecology, Psychiatry, Euclidean distance, Diagnosis |
| Abstract: | A Case-Based Reasoning (CBR) system for medical diagnosis mimics the way doctors make a diagnosis. Given a new case, its accuracy in practice depends on successful retrieval of similar cases. CBR systems have had some success in dealing with simple diseases because of the robustness of their case base. However, their diagnostic accuracy suffers when dealing with complex diseases particularly those that involve multiple domains in medicine. An example of such a condition is Premenstrual syndrome (PMS) as it falls under both gynaecology and psychiatry. To address this issue, the paper proposes a CBR-based expert system that uses the K-nearest neighbour (KNN) algorithm to search k similar cases based on the Euclidean distance measure. The novelty of the system is in the design of a flexible auto-set tolerance (T), which serves as a threshold to extract cases for which similarities are greater than the assigned value of T. A prototype software tool with a menu-driven Graphical User Interface (GUI) has been developed for case input, analysis of results, and case adaptation within the system. Finally, the performance of the tool has been checked on a set of real-world PMS cases. [ABSTRACT FROM AUTHOR] |
| Copyright of Expert Systems 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: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 85189340 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Case-Based Reasoning system for complex medical diagnosis. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Chattopadhyay%2C+Subhagata%22">Chattopadhyay, Subhagata</searchLink><relatesTo>1</relatesTo><i> subhagatachatterjee@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Banerjee%2C+Suvendu%22">Banerjee, Suvendu</searchLink><relatesTo>2</relatesTo><i> suvendu_banerjee@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Rabhi%2C+Fethi+A%2E%22">Rabhi, Fethi A.</searchLink><relatesTo>3</relatesTo><i> f.rabhi@unsw.edu.au</i><br /><searchLink fieldCode="AR" term="%22Acharya%2C+U%2E+Rajendra%22">Acharya, U. Rajendra</searchLink><relatesTo>4</relatesTo><i> aru@np.edu.sg</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Expert+Systems%22">Expert Systems</searchLink>. Feb2013, Vol. 30 Issue 1, p12-20. 9p. 1 Color Photograph, 3 Diagrams, 3 Charts, 1 Graph. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Case-based+reasoning%22">Case-based reasoning</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+diagnostic+software%22">Computer diagnostic software</searchLink><br /><searchLink fieldCode="DE" term="%22Premenstrual+syndrome%22">Premenstrual syndrome</searchLink><br /><searchLink fieldCode="DE" term="%22Information+retrieval%22">Information retrieval</searchLink><br /><searchLink fieldCode="DE" term="%22Gynecology%22">Gynecology</searchLink><br /><searchLink fieldCode="DE" term="%22Psychiatry%22">Psychiatry</searchLink><br /><searchLink fieldCode="DE" term="%22Euclidean+distance%22">Euclidean distance</searchLink><br /><searchLink fieldCode="DE" term="%22Diagnosis%22">Diagnosis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: A Case-Based Reasoning (CBR) system for medical diagnosis mimics the way doctors make a diagnosis. Given a new case, its accuracy in practice depends on successful retrieval of similar cases. CBR systems have had some success in dealing with simple diseases because of the robustness of their case base. However, their diagnostic accuracy suffers when dealing with complex diseases particularly those that involve multiple domains in medicine. An example of such a condition is Premenstrual syndrome (PMS) as it falls under both gynaecology and psychiatry. To address this issue, the paper proposes a CBR-based expert system that uses the K-nearest neighbour (KNN) algorithm to search k similar cases based on the Euclidean distance measure. The novelty of the system is in the design of a flexible auto-set tolerance (T), which serves as a threshold to extract cases for which similarities are greater than the assigned value of T. A prototype software tool with a menu-driven Graphical User Interface (GUI) has been developed for case input, analysis of results, and case adaptation within the system. Finally, the performance of the tool has been checked on a set of real-world PMS cases. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Expert Systems 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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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/j.1468-0394.2012.00618.x Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 12 Subjects: – SubjectFull: Case-based reasoning Type: general – SubjectFull: Computer diagnostic software Type: general – SubjectFull: Premenstrual syndrome Type: general – SubjectFull: Information retrieval Type: general – SubjectFull: Gynecology Type: general – SubjectFull: Psychiatry Type: general – SubjectFull: Euclidean distance Type: general – SubjectFull: Diagnosis Type: general Titles: – TitleFull: A Case-Based Reasoning system for complex medical diagnosis. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Chattopadhyay, Subhagata – PersonEntity: Name: NameFull: Banerjee, Suvendu – PersonEntity: Name: NameFull: Rabhi, Fethi A. – PersonEntity: Name: NameFull: Acharya, U. Rajendra IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2013 Type: published Y: 2013 Identifiers: – Type: issn-print Value: 02664720 Numbering: – Type: volume Value: 30 – Type: issue Value: 1 Titles: – TitleFull: Expert Systems Type: main |
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