Computing a weighted jaccard index of electronic medical record for disease prediction

Chia Hui Huang, Yun-Te Liao, David Taniar, Tun-Wen Pai

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. Patient’s spinal cord, brainstem, or motor cortex of the cerebral motor cortex are gradually degenerated and lead to systemic muscle atrophy and weakness. Medicine therapies used for treating ALS mainly focus on symptomatic treatment and delaying deterioration. At present, no precise treatment can effectively cure, halt, or reverse the progression of ALS disease. Therefore, it is extremely important to predict high-risk populations of ALS candidates and prevent from the early stages. This research analyzes the historical medical records of ALS patients from the Taiwan National Health Insurance Research Database (NHIRD). Through analyzing comorbidity within a specific time interval, we proposed a novel index, weighted Jaccard index, for effective prediction analyses. The weighted Jaccard index and logistic regression model were applied to build an ALS patient prediction system. Based on comparing electronic medical records testing subject and know ALS patient, we can effectively detect potential ALS patients at early stages. Early and accurate detection can provide medical doctors to conduct precise inspection and appropriate treatment with efficient and effective guidelines for decision making.

Original languageEnglish
Title of host publicationTrends in Artificial Intelligence Theory and Applications - Artificial Intelligence Practices
Subtitle of host publication33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020 Kitakyushu, Japan, September 22–25, 2020 Proceedings
EditorsHamido Fujita, Philippe Fournier-Viger, Moonis Ali, Jun Sasaki
Place of PublicationCham Switzerland
PublisherSpringer
Pages445-456
Number of pages12
ISBN (Electronic)9783030557898
ISBN (Print)9783030557881
DOIs
Publication statusPublished - 2020
EventInternational Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems 2020 - Kitakyushu, Japan
Duration: 22 Sep 202025 Sep 2020
Conference number: 33rd
https://link.springer.com/book/10.1007/978-3-030-55789-8 (Proceedings)
https://jsasaki3.wixsite.com/ieaaie2020 (Website)

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume12144
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems 2020
Abbreviated titleIEA/AIE 2020
CountryJapan
CityKitakyushu
Period22/09/2025/09/20
Internet address

Keywords

  • ALS
  • Disease prediction
  • Electronic medical record (EMR)
  • Secondary data
  • Weighted Jaccard index

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