Information Extraction from German Clinical Care Documents in Context of Alzheimer’s Disease

Dementia affects approximately 50 million people in the world today, the majority suffering from Alzheimer’s disease (AD). The availability of long-term patient data is one of the most important prerequisites for a better understanding of diseases. Worldwide, many prospective, longitudinal cohort st...

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Autores principales:	Lisa Langnickel, Kilian Krockauer, Mischa Uebachs, Sebastian Schaaf, Sumit Madan, Thomas Klockgether, Juliane Fluck
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	clinical text mining data standardization semantic interoperability Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/bb272cb5353746e9850472796636a274
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spelling	oai:doaj.org-article:bb272cb5353746e9850472796636a2742021-11-25T16:36:20ZInformation Extraction from German Clinical Care Documents in Context of Alzheimer’s Disease10.3390/app1122107172076-3417https://doaj.org/article/bb272cb5353746e9850472796636a2742021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10717https://doaj.org/toc/2076-3417Dementia affects approximately 50 million people in the world today, the majority suffering from Alzheimer’s disease (AD). The availability of long-term patient data is one of the most important prerequisites for a better understanding of diseases. Worldwide, many prospective, longitudinal cohort studies have been initiated to understand AD. However, this approach takes years to enroll and follow up with a substantial number of patients, resulting in a current lack of data. This raises the question of whether clinical routine datasets could be utilized to extend collected registry data. It is, therefore, necessary to assess what kind of information is available in memory clinic routine databases. We did exactly this based on the example of the University Hospital Bonn. Whereas a number of data items are available in machine readable formats, additional valuable information is stored in textual documents. The extraction of information from such documents is only applicable via text mining methods. Therefore, we set up modular, rule-based text mining workflows requiring minimal sets of training data. The system achieves F1-scores over 95% for the most relevant classes, i.e., memory disturbances from medical reports and quantitative scores from semi-structured neuropsychological test protocols. Thus, we created a machine-readable core dataset for over 8000 patient visits over a ten-year period.Lisa LangnickelKilian KrockauerMischa UebachsSebastian SchaafSumit MadanThomas KlockgetherJuliane FluckMDPI AGarticleclinical text miningdata standardizationsemantic interoperabilityTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10717, p 10717 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	clinical text mining data standardization semantic interoperability Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	clinical text mining data standardization semantic interoperability Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Lisa Langnickel Kilian Krockauer Mischa Uebachs Sebastian Schaaf Sumit Madan Thomas Klockgether Juliane Fluck Information Extraction from German Clinical Care Documents in Context of Alzheimer’s Disease
description	Dementia affects approximately 50 million people in the world today, the majority suffering from Alzheimer’s disease (AD). The availability of long-term patient data is one of the most important prerequisites for a better understanding of diseases. Worldwide, many prospective, longitudinal cohort studies have been initiated to understand AD. However, this approach takes years to enroll and follow up with a substantial number of patients, resulting in a current lack of data. This raises the question of whether clinical routine datasets could be utilized to extend collected registry data. It is, therefore, necessary to assess what kind of information is available in memory clinic routine databases. We did exactly this based on the example of the University Hospital Bonn. Whereas a number of data items are available in machine readable formats, additional valuable information is stored in textual documents. The extraction of information from such documents is only applicable via text mining methods. Therefore, we set up modular, rule-based text mining workflows requiring minimal sets of training data. The system achieves F1-scores over 95% for the most relevant classes, i.e., memory disturbances from medical reports and quantitative scores from semi-structured neuropsychological test protocols. Thus, we created a machine-readable core dataset for over 8000 patient visits over a ten-year period.
format	article
author	Lisa Langnickel Kilian Krockauer Mischa Uebachs Sebastian Schaaf Sumit Madan Thomas Klockgether Juliane Fluck
author_facet	Lisa Langnickel Kilian Krockauer Mischa Uebachs Sebastian Schaaf Sumit Madan Thomas Klockgether Juliane Fluck
author_sort	Lisa Langnickel
title	Information Extraction from German Clinical Care Documents in Context of Alzheimer’s Disease
title_short	Information Extraction from German Clinical Care Documents in Context of Alzheimer’s Disease
title_full	Information Extraction from German Clinical Care Documents in Context of Alzheimer’s Disease
title_fullStr	Information Extraction from German Clinical Care Documents in Context of Alzheimer’s Disease
title_full_unstemmed	Information Extraction from German Clinical Care Documents in Context of Alzheimer’s Disease
title_sort	information extraction from german clinical care documents in context of alzheimer’s disease
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/bb272cb5353746e9850472796636a274
work_keys_str_mv	AT lisalangnickel informationextractionfromgermanclinicalcaredocumentsincontextofalzheimersdisease AT kiliankrockauer informationextractionfromgermanclinicalcaredocumentsincontextofalzheimersdisease AT mischauebachs informationextractionfromgermanclinicalcaredocumentsincontextofalzheimersdisease AT sebastianschaaf informationextractionfromgermanclinicalcaredocumentsincontextofalzheimersdisease AT sumitmadan informationextractionfromgermanclinicalcaredocumentsincontextofalzheimersdisease AT thomasklockgether informationextractionfromgermanclinicalcaredocumentsincontextofalzheimersdisease AT julianefluck informationextractionfromgermanclinicalcaredocumentsincontextofalzheimersdisease
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Information Extraction from German Clinical Care Documents in Context of Alzheimer’s Disease

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