Asthma Risk Factor

Citation Author(s):
Eman
alharbi
Department of computer science and artificial intelligent, Umm Al-Qura University, Makkah, SA
Submitted by:
Eman Alharbi
Last updated:
Fri, 05/03/2024 - 14:47
DOI:
10.21227/n60r-pz37
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Abstract 

Asthma is a common respiratory disease that affects people in many countries. It causes an attack that harms those patients and can cause death. This attack is related to many risk factors, including biosignals and environmental conditions. Here, we provide a dataset (584 entries) on the asthma biosignals and environmental conditions. This dataset was collected from 21 participants who have different levels of asthma disease. It was collected from the Makkah region in Saudi Arabia (Makkah and Jeddah cities) for three months, from 24-march – 30-June 2021. We introduce an analysis for feature importance by using a decision tree classifier and logistic regression. The coefficient scores of these classifiers indicate the most relevant features which can contribute to an asthma attack. These analyses provide insights into which input features can contribute through building machine-learning asthma attacks prediction models.

Instructions: 

this data was recorded to understand the effective risk factor on having asthma attack. The collected factors including 30 attributes, 13 are historical health records, 13 are daily symptoms, and 4 environmental attributes. 

Comments

hi, can you please upload dataset?

Submitted by Ivan Vassilenko on Wed, 05/01/2024 - 09:30

Hi,

Could you please share the data?

Thank you. 

Submitted by Fouzi Harrou on Thu, 05/02/2024 - 08:02

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