“DTH 1.0”: TOWARDS AN ARTIFICIAL INTELLIGENCE DECISION SUPPORT SYSTEM FOR GEOGRAPHICAL ANALYSIS OF HEALTH DATA
The complexity of modern scientific research requires advanced approaches to handle and analyse rich and dynamic data. Organizations such as hospitals, hold a great number of health datasets which may consist of many individual records. Artificial Intelligence methodologies incorporate approaches f...
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| Format: | Article |
| Language: | English |
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European Association of Geographers
2013-10-01
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| Series: | European Journal of Geography |
| Online Access: | https://www.eurogeojournal.eu/index.php/egj/article/view/527 |
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| author | Dimitris KAVROUDAKIS Phaedon C. KYRIAKIDIS |
| author_facet | Dimitris KAVROUDAKIS Phaedon C. KYRIAKIDIS |
| author_sort | Dimitris KAVROUDAKIS |
| collection | DOAJ |
| description |
The complexity of modern scientific research requires advanced approaches to handle and
analyse rich and dynamic data. Organizations such as hospitals, hold a great number of health
datasets which may consist of many individual records. Artificial Intelligence methodologies
incorporate approaches for knowledge retrieval and pattern discovery, which have been
proven to be useful for data analysis in various disciplines. Decision trees methods belong to
knowledge discovery methodologies and use computational algorithms for the extraction of
patterns from data. This work describes the development of an autonomous Decision Support
System (“Dth 1.0”) for the real-time analysis of health data with the use of decision trees. The
proposed system uses a patient's dataset based on the patients’ symptoms and other relevant
information and prepares reports about the importance of the characteristics that determine
the number of patients of a specific disease. This work presents the basic concept of decision
trees, describes the design of a tree-based system and uses a virtual database to illustrate the
classification of patients in a hypothetical intra-hospital case study.
|
| format | Article |
| id | doaj-art-0fd5aea21d8249d599b5266d88c6f46b |
| institution | Kabale University |
| issn | 1792-1341 2410-7433 |
| language | English |
| publishDate | 2013-10-01 |
| publisher | European Association of Geographers |
| record_format | Article |
| series | European Journal of Geography |
| spelling | doaj-art-0fd5aea21d8249d599b5266d88c6f46b2025-01-01T06:58:22ZengEuropean Association of GeographersEuropean Journal of Geography1792-13412410-74332013-10-0143“DTH 1.0”: TOWARDS AN ARTIFICIAL INTELLIGENCE DECISION SUPPORT SYSTEM FOR GEOGRAPHICAL ANALYSIS OF HEALTH DATADimitris KAVROUDAKIS0Phaedon C. KYRIAKIDIS1University of the Aegean, Geography Department, University Hill, Mytilene, GreeceUniversity of the Aegean, Geography Department, University Hill, Mytilene, Greece The complexity of modern scientific research requires advanced approaches to handle and analyse rich and dynamic data. Organizations such as hospitals, hold a great number of health datasets which may consist of many individual records. Artificial Intelligence methodologies incorporate approaches for knowledge retrieval and pattern discovery, which have been proven to be useful for data analysis in various disciplines. Decision trees methods belong to knowledge discovery methodologies and use computational algorithms for the extraction of patterns from data. This work describes the development of an autonomous Decision Support System (“Dth 1.0”) for the real-time analysis of health data with the use of decision trees. The proposed system uses a patient's dataset based on the patients’ symptoms and other relevant information and prepares reports about the importance of the characteristics that determine the number of patients of a specific disease. This work presents the basic concept of decision trees, describes the design of a tree-based system and uses a virtual database to illustrate the classification of patients in a hypothetical intra-hospital case study. https://www.eurogeojournal.eu/index.php/egj/article/view/527 |
| spellingShingle | Dimitris KAVROUDAKIS Phaedon C. KYRIAKIDIS “DTH 1.0”: TOWARDS AN ARTIFICIAL INTELLIGENCE DECISION SUPPORT SYSTEM FOR GEOGRAPHICAL ANALYSIS OF HEALTH DATA European Journal of Geography |
| title | “DTH 1.0”: TOWARDS AN ARTIFICIAL INTELLIGENCE DECISION SUPPORT SYSTEM FOR GEOGRAPHICAL ANALYSIS OF HEALTH DATA |
| title_full | “DTH 1.0”: TOWARDS AN ARTIFICIAL INTELLIGENCE DECISION SUPPORT SYSTEM FOR GEOGRAPHICAL ANALYSIS OF HEALTH DATA |
| title_fullStr | “DTH 1.0”: TOWARDS AN ARTIFICIAL INTELLIGENCE DECISION SUPPORT SYSTEM FOR GEOGRAPHICAL ANALYSIS OF HEALTH DATA |
| title_full_unstemmed | “DTH 1.0”: TOWARDS AN ARTIFICIAL INTELLIGENCE DECISION SUPPORT SYSTEM FOR GEOGRAPHICAL ANALYSIS OF HEALTH DATA |
| title_short | “DTH 1.0”: TOWARDS AN ARTIFICIAL INTELLIGENCE DECISION SUPPORT SYSTEM FOR GEOGRAPHICAL ANALYSIS OF HEALTH DATA |
| title_sort | dth 1 0 towards an artificial intelligence decision support system for geographical analysis of health data |
| url | https://www.eurogeojournal.eu/index.php/egj/article/view/527 |
| work_keys_str_mv | AT dimitriskavroudakis dth10towardsanartificialintelligencedecisionsupportsystemforgeographicalanalysisofhealthdata AT phaedonckyriakidis dth10towardsanartificialintelligencedecisionsupportsystemforgeographicalanalysisofhealthdata |