Korean Standard Classification of Functioning, Disability and Health (KCF) Code Linking on Natural Language with Extract Algorithm (자연어 알고리즘을 활용한 한국표준건강분류(KCF) 코드 검색)

Choi, Nyeon Sik (최년식); Song Ju-min (송주민)

Korean Standard Classification of Functioning, Disability and Health (KCF) Code Linking on Natural Language with Extract Algorithm

Journal of the Korean Society of Physical Medicine
Abbr : J Korean Soc Phys Med
2023, 18(1), pp.77-86
Publisher : The Korean Society of Physical Medicine
Research Area : Medicine and Pharmacy > Physical Therapy > Other physical therapy
Received : January 30, 2023
Accepted : February 9, 2023
Published : February 28, 2023

Choi, Nyeon Sik ¹, Song Ju-min ¹

¹신라대학교

Accredited

ABSTRACT

PURPOSE: This study developed an experimental algorithm, which is similar or identical to semantic linking for KCF codes, even if it converted existing semantic code linking methods to morphological code extraction methods. The purpose of this study was to verify the applicability of the system. METHODS: An experimental algorithm was developed as a morphological extraction method using code-specific words in the KCF code descriptions. The algorithm was designed in five stages that extracted KCF code using natural language paragraphs. For verification, 80 clinical natural language experimental cases were defined. Data acquisition for the study was conducted with the deliberation and approval of the bioethics committee of the relevant institution. Each case was linked by experts and was extracted through the System. The linking accuracy index model was used to compare the KCF code linking by experts with those extracted from the system. RESULTS: The accuracy was checked using the linking accuracy index model for each case. The analysis was divided into five sections using the accuracy range. The section with less than 25% was compared; the first experimental accuracy was 61.24%. In the second, the accuracy was 42.50%. The accuracy was improved to 30.59% in the section by only a weight adjustment. The accuracy can be improved by adjusting several independent variables applied to the system. CONCLUSION: This paper suggested and verified a way to easily extract and utilize KCF codes even if they are not experts. KCF requires the system for utilization, and additional study will be needed.

KEYWORDS

Code extraction algorithm, Code search, KCF, Linking, Natural language

Citation status

* References for papers published after 2023 are currently being built.

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