AI powered asthma prediction towards treatment formulation : An android app approach

Asthma is a disease which attacks the lungs and that affects people of all ages. Asthma prediction is crucial since many individuals already have asthma and increasing asthma patients is continuous. Machine learning (ML) has been demonstrated to help individuals make judgments and predictions based...

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Main Authors: Murad, Saydul Akbar, Adhikary, Apurba, Muzahid, Abu Jafar Md, Sarker, Md. Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md.
Format: Article
Language:English
Published: Tech Science Press 2022
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/34959/
http://umpir.ump.edu.my/id/eprint/34959/1/AI%20powered%20asthma%20prediction%20towards%20treatment%20formulation_An%20android%20app%20approach.pdf
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author Murad, Saydul Akbar
Adhikary, Apurba
Muzahid, Abu Jafar Md
Sarker, Md. Murad Hossain
Khan, Md. Ashikur Rahman
Hossain, Md. Bipul
Bairagi, Anupam Kumar
Masud, Mehedi
Kowsher, Md.
author_facet Murad, Saydul Akbar
Adhikary, Apurba
Muzahid, Abu Jafar Md
Sarker, Md. Murad Hossain
Khan, Md. Ashikur Rahman
Hossain, Md. Bipul
Bairagi, Anupam Kumar
Masud, Mehedi
Kowsher, Md.
author_sort Murad, Saydul Akbar
building UMP Institutional Repository
collection Online Access
description Asthma is a disease which attacks the lungs and that affects people of all ages. Asthma prediction is crucial since many individuals already have asthma and increasing asthma patients is continuous. Machine learning (ML) has been demonstrated to help individuals make judgments and predictions based on vast amounts of data. Because Android applications are widely available, it will be highly beneficial to individuals if they can receive therapy through a simple app. In this study, the machine learning approach is utilized to determine whether or not a person is affected by asthma. Besides, an android application is being cre-ated to give therapy based on machine learning predictions. To collect data, we enlisted the help of 4,500 people. We collect information on 23 asthma-related characteristics. We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.
first_indexed 2025-11-15T03:16:22Z
format Article
id ump-34959
institution Universiti Malaysia Pahang
institution_category Local University
language English
last_indexed 2025-11-15T03:16:22Z
publishDate 2022
publisher Tech Science Press
recordtype eprints
repository_type Digital Repository
spelling ump-349592022-10-27T01:04:03Z http://umpir.ump.edu.my/id/eprint/34959/ AI powered asthma prediction towards treatment formulation : An android app approach Murad, Saydul Akbar Adhikary, Apurba Muzahid, Abu Jafar Md Sarker, Md. Murad Hossain Khan, Md. Ashikur Rahman Hossain, Md. Bipul Bairagi, Anupam Kumar Masud, Mehedi Kowsher, Md. QA75 Electronic computers. Computer science QA76 Computer software TA Engineering (General). Civil engineering (General) Asthma is a disease which attacks the lungs and that affects people of all ages. Asthma prediction is crucial since many individuals already have asthma and increasing asthma patients is continuous. Machine learning (ML) has been demonstrated to help individuals make judgments and predictions based on vast amounts of data. Because Android applications are widely available, it will be highly beneficial to individuals if they can receive therapy through a simple app. In this study, the machine learning approach is utilized to determine whether or not a person is affected by asthma. Besides, an android application is being cre-ated to give therapy based on machine learning predictions. To collect data, we enlisted the help of 4,500 people. We collect information on 23 asthma-related characteristics. We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform. Tech Science Press 2022 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/34959/1/AI%20powered%20asthma%20prediction%20towards%20treatment%20formulation_An%20android%20app%20approach.pdf Murad, Saydul Akbar and Adhikary, Apurba and Muzahid, Abu Jafar Md and Sarker, Md. Murad Hossain and Khan, Md. Ashikur Rahman and Hossain, Md. Bipul and Bairagi, Anupam Kumar and Masud, Mehedi and Kowsher, Md. (2022) AI powered asthma prediction towards treatment formulation : An android app approach. Intelligent Automation and Soft Computing, 34 (1). pp. 87-103. ISSN 1079-8587. (Published) https://doi.org/10.32604/iasc.2022.024777 https://doi.org/10.32604/iasc.2022.024777
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
TA Engineering (General). Civil engineering (General)
Murad, Saydul Akbar
Adhikary, Apurba
Muzahid, Abu Jafar Md
Sarker, Md. Murad Hossain
Khan, Md. Ashikur Rahman
Hossain, Md. Bipul
Bairagi, Anupam Kumar
Masud, Mehedi
Kowsher, Md.
AI powered asthma prediction towards treatment formulation : An android app approach
title AI powered asthma prediction towards treatment formulation : An android app approach
title_full AI powered asthma prediction towards treatment formulation : An android app approach
title_fullStr AI powered asthma prediction towards treatment formulation : An android app approach
title_full_unstemmed AI powered asthma prediction towards treatment formulation : An android app approach
title_short AI powered asthma prediction towards treatment formulation : An android app approach
title_sort ai powered asthma prediction towards treatment formulation : an android app approach
topic QA75 Electronic computers. Computer science
QA76 Computer software
TA Engineering (General). Civil engineering (General)
url http://umpir.ump.edu.my/id/eprint/34959/
http://umpir.ump.edu.my/id/eprint/34959/
http://umpir.ump.edu.my/id/eprint/34959/
http://umpir.ump.edu.my/id/eprint/34959/1/AI%20powered%20asthma%20prediction%20towards%20treatment%20formulation_An%20android%20app%20approach.pdf