Correlation between laboratory characteristics and clinical degree of dengue as an initial stage in a development of machine learning predictor program

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Abstract

Dengue is one of the endemic diseases in Indonesia. Dengue is being suffered by many people, regardless of their gender and age. Therefore, a research about dengue based on a dengue patients’ data is conducted. There was a lot of information written in that data regarding the corresponding patients and the dengue they had suffered, such as gender, age, how long the patients were hospitalized, the symptoms they experienced, and laboratory characteristics. The diagnosis of each of the corresponding patients based on the symptoms and laboratory characteristics were also written in that data. The diagnoses were classified into three different clinical degrees according to the severity level, which are DF as the mild level, DHF grade 1 as the intermediate level, and DHF grade 2 as the severe level. In this research, data of the patients on the third day of being hospitalized is analyzed, because on the third day, dengue is entering a critical phase. The objectives of this research are: i) to find laboratory characteristics that affect the clinical degree of dengue in the critical phase, and ii) to analyze how robust the impact of those laboratory characteristics on the clinical degree of dengue in the critical phase. In this research, Bivariate Analysis was applied as the method to find the solution of the analyzed problems. The results obtained from this research can give information for the physicians about laboratory characteristics that affect the clinical degree of dengue in the critical phase, and how robust the impact of those laboratory characteristics on the clinical degree of dengue in the critical phase. Those results also can help the physicians to find solutions or strategies in preventing and/or treating dengue. Furthermore, those results will be used in the development of Machine Learning predictor program which will be able to predict the clinical degree of dengue in the critical phase, if the laboratory characteristics are known.

Original languageEnglish
Title of host publicationSymposium on Biomathematics 2019, SYMOMATH 2019
EditorsMochamad Apri, Vitalii Akimenko
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735420243
DOIs
Publication statusPublished - 22 Sep 2020
EventSymposium on Biomathematics 2019, SYMOMATH 2019 - Bali, Indonesia
Duration: 25 Aug 201928 Aug 2019

Publication series

NameAIP Conference Proceedings
Volume2264
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

ConferenceSymposium on Biomathematics 2019, SYMOMATH 2019
Country/TerritoryIndonesia
CityBali
Period25/08/1928/08/19

Keywords

  • Bivariate analysis
  • Clinical degree
  • Dengue
  • Diagnosis
  • Laboratory characteristics

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