Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)

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Comparative Study of Lung Disease Prediction System Using Top 10 Data Mining Algorithms with Real Clinical Medical Records

Authors
I Ketut Agung Enriko1, *, Teuku Muda Mahuzza1, Sevia Indah Purnama1, Dadang Gunawan2
1Institut Teknologi Telkom Purwokerto, Purwokerto, Indonesia
2University of Indonesia, West Java, Indonesia
*Corresponding author. Email: enriko@ittelkom-pwt.ac.id
Corresponding Author
I Ketut Agung Enriko
Available Online 26 December 2022.
DOI
10.2991/978-94-6463-084-8_24How to use a DOI?
Keywords
machine learning; lung disease prediction; binary prediction; Naïve Bayes; k-Nearest Neighbor First Section
Abstract

These years, the use of machine learning for disease prediction is blooming. Meanwhile, lung disease is one of the deadliest diseases in the world. Many researchers have been doing research on lung disease predictions using various techniques. In this study, ten machine learning algorithms are used for comparative study in lung disease prediction. The dataset is collected from a hospital in Banda Aceh, Indonesia, consisting of 300 data. The parameters included in the dataset are: symptoms, body temperature, respiration rate, oxygen saturation, blood pressure, heart rate, sex, and age. This dataset needs to be pre-processed and then analyzed using those top 10 machine learning algorithms. The prediction will be whether a patient gets a lung disease or not (binary prediction). The result shows that Naïve Bayes and k-Nearest Neighbor are the best choices among those algorithms in terms of accuracy and speed.

Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)
Series
Advances in Computer Science Research
Publication Date
26 December 2022
ISBN
978-94-6463-084-8
ISSN
2352-538X
DOI
10.2991/978-94-6463-084-8_24How to use a DOI?
Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - I Ketut Agung Enriko
AU  - Teuku Muda Mahuzza
AU  - Sevia Indah Purnama
AU  - Dadang Gunawan
PY  - 2022
DA  - 2022/12/26
TI  - Comparative Study of Lung Disease Prediction System Using Top 10 Data Mining Algorithms with Real Clinical Medical Records
BT  - Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)
PB  - Atlantis Press
SP  - 269
EP  - 281
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-084-8_24
DO  - 10.2991/978-94-6463-084-8_24
ID  - Enriko2022
ER  -