Neurodegenerative clinical records analyzer: detection of recurrent patterns within clinical records towards the identification of typical signs of neurodegenerative disease history
When treating structured health-system-related knowledge, the establishment of an over-dimension to guide the separation of entities becomes essential. This is consistent with the information retrieval processes aimed at defining a coherent and dynamic way – meaning by that the multilevel integrati...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Firenze University Press
2023-05-01
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| Series: | JLIS.it |
| Subjects: | |
| Online Access: | https://jlis.it/index.php/jlis/article/view/522 |
| _version_ | 1797826622421729280 |
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| author | Erika Pasceri Mérième Bouhandi Claudia Lanza Anna Perri Valentina Laganà Raffaele Maletta Raffaele Di Lorenzo Amalia C. Bruni |
| author_facet | Erika Pasceri Mérième Bouhandi Claudia Lanza Anna Perri Valentina Laganà Raffaele Maletta Raffaele Di Lorenzo Amalia C. Bruni |
| author_sort | Erika Pasceri |
| collection | DOAJ |
| description |
When treating structured health-system-related knowledge, the establishment of an over-dimension to guide the separation of entities becomes essential. This is consistent with the information retrieval processes aimed at defining a coherent and dynamic way – meaning by that the multilevel integration of medical textual inputs and computational interpretation – to replicate the flow of data inserted in the clinical records. This study presents a strategic technique to categorize the clinical entities related to patients affected by neurodegenerative diseases. After a pre-processing range of tasks over paper-based and handwritten medical records, and through subsequent machine learning and, more specifically, natural language processing operations over the digitized clinical records, the research activity provides a semantic support system to detect the main symptoms and locate them in the appropriate clusters. Finally, the supervision of the experts proved to be essential in the correspondence sequence configuration aimed at providing an automatic reading of the clinical records according to the clinical data that is needed to predict the detection of neurodegenerative disease symptoms.
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| first_indexed | 2024-04-09T12:35:21Z |
| format | Article |
| id | doaj.art-607ec6af295c46ebac2a1b52bca177ea |
| institution | Directory Open Access Journal |
| issn | 2038-1026 |
| language | English |
| last_indexed | 2024-04-09T12:35:21Z |
| publishDate | 2023-05-01 |
| publisher | Firenze University Press |
| record_format | Article |
| series | JLIS.it |
| spelling | doaj.art-607ec6af295c46ebac2a1b52bca177ea2023-05-15T15:25:24ZengFirenze University PressJLIS.it2038-10262023-05-0114210.36253/jlis.it-522Neurodegenerative clinical records analyzer: detection of recurrent patterns within clinical records towards the identification of typical signs of neurodegenerative disease historyErika Pasceri0Mérième Bouhandi1Claudia Lanza2Anna Perri3Valentina Laganà4Raffaele Maletta5Raffaele Di Lorenzo6Amalia C. Bruni7University of CalabriaUniversity of NantesUniversity of CalabriaUniversity of CalabriaAssociation for Neurogenetic Research (ARN)Regional Neurogenetic Centre, ASPRegional Neurogenetic Centre, ASPRegional Neurogenetic Centre, ASP When treating structured health-system-related knowledge, the establishment of an over-dimension to guide the separation of entities becomes essential. This is consistent with the information retrieval processes aimed at defining a coherent and dynamic way – meaning by that the multilevel integration of medical textual inputs and computational interpretation – to replicate the flow of data inserted in the clinical records. This study presents a strategic technique to categorize the clinical entities related to patients affected by neurodegenerative diseases. After a pre-processing range of tasks over paper-based and handwritten medical records, and through subsequent machine learning and, more specifically, natural language processing operations over the digitized clinical records, the research activity provides a semantic support system to detect the main symptoms and locate them in the appropriate clusters. Finally, the supervision of the experts proved to be essential in the correspondence sequence configuration aimed at providing an automatic reading of the clinical records according to the clinical data that is needed to predict the detection of neurodegenerative disease symptoms. https://jlis.it/index.php/jlis/article/view/522AlzheimerCategorizationElectronic health records (EHR)Machine learningSemantic annotation |
| spellingShingle | Erika Pasceri Mérième Bouhandi Claudia Lanza Anna Perri Valentina Laganà Raffaele Maletta Raffaele Di Lorenzo Amalia C. Bruni Neurodegenerative clinical records analyzer: detection of recurrent patterns within clinical records towards the identification of typical signs of neurodegenerative disease history JLIS.it Alzheimer Categorization Electronic health records (EHR) Machine learning Semantic annotation |
| title | Neurodegenerative clinical records analyzer: detection of recurrent patterns within clinical records towards the identification of typical signs of neurodegenerative disease history |
| title_full | Neurodegenerative clinical records analyzer: detection of recurrent patterns within clinical records towards the identification of typical signs of neurodegenerative disease history |
| title_fullStr | Neurodegenerative clinical records analyzer: detection of recurrent patterns within clinical records towards the identification of typical signs of neurodegenerative disease history |
| title_full_unstemmed | Neurodegenerative clinical records analyzer: detection of recurrent patterns within clinical records towards the identification of typical signs of neurodegenerative disease history |
| title_short | Neurodegenerative clinical records analyzer: detection of recurrent patterns within clinical records towards the identification of typical signs of neurodegenerative disease history |
| title_sort | neurodegenerative clinical records analyzer detection of recurrent patterns within clinical records towards the identification of typical signs of neurodegenerative disease history |
| topic | Alzheimer Categorization Electronic health records (EHR) Machine learning Semantic annotation |
| url | https://jlis.it/index.php/jlis/article/view/522 |
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