## 4 Pre-Processing and Classification
### Pre-Processing
\begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Data Source** & **Advantage** & **Disadvantage** & **Accessibility** & **Weblink** \\ \hline Disease symptoms & Organized list of diseases including lungs and asthma with associated symptoms & Lack of detail for the patient demographics & Public & [[https://www.kaggle.com/datasets/dhivyeshrk/diseases-and-symptoms-dataset](https://www.kaggle.com/datasets/dhivyeshrk/diseases-and-symptoms-dataset)]([https://www.kaggle.com/datasets/dhivyeshrk/diseases-and-symptoms-dataset](https://www.kaggle.com/datasets/dhivyeshrk/diseases-and-symptoms-dataset)) (accessed on 15 January 2025) \\ \hline OpenWeather map & Provides several weather data parameters useful in asthma-environment prediction & Application programmable interface (API) is required with limited usage & Public & [[https://openweathermap.org/](https://openweathermap.org/)]([https://openweathermap.org/](https://openweathermap.org/)) (accessed on 15 January 2025) \\ \hline Hospitals’ EHRs & Offers multi-modal data containing laboratory, treatment, clinical and medical history & Management, acquisition, and interpretation is difficult, requiring expertise & Public, Private & MIMIC, eICU collaborative database, TriNetX, Epic Cosmos \\ \hline Chest radiographs & Provides huge amount of chest X-ray images useful in respiratory disease analysis including asthma & Major sampling focus is pneumonia with a lack of other conditions & Public & [[https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia](https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia)]([https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia](https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia)) (accessed on 15 January 2025) \\ \hline Pollution data & Air quality data access for multiple Indian locations in real time & Data availability and details may be limited with respect to provided regions & Public & [[https://cpch.nicin/real-time-air-quality-data/](https://cpch.nicin/real-time-air-quality-data/)]([https://cpch.nicin/real-time-air-quality-data/](https://cpch.nicin/real-time-air-quality-data/)) (accessed on 15 January 2025) \\ \hline Respiratory sound & Multiple respiratory audio recordings offering deep analysis including asthma & Data annotations may be needed with careful interpretation & Public & [[https://www.kaggle.com/datasets/vbookshelf/respiratory-sound-database](https://www.kaggle.com/datasets/vbookshelf/respiratory-sound-database)]([https://www.kaggle.com/datasets/vbookshelf/respiratory-sound-database](https://www.kaggle.com/datasets/vbookshelf/respiratory-sound-database)) (accessed on 15 January 2025) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary of the databases useful in asthma and how it concerns weather prediction. matrix for selecting key features. [PERSON] et al. [33] applied the 'analysis of variance' test to assess the statistical significance of attributes. [PERSON] et al. [58] employed Kernel principal component analysis, a non-linear dimensionality reduction technique, for feature selection. [PERSON] et al. [27] utilized the Chi-squared test for effective feature selection. [PERSON] et al. [36] have separated the features into categorical and continuous values and [PERSON] et al. [59] performed data aggregation by integrating multiple data sources. Finally, model hyper-parameter tuning, crucial for optimizing performance, was carried out by [PERSON] et al. [42] using the Bayesian optimization method.