## 4 Data Set  
The data set used within the presented case study was collected at Specialised Hospital No. 1 in Bytom, Poland, between 21 February 2020 and 30 September 2020, thanks to the cooperation of hospital staff and data scientists involved in the project.  
Data acquisition was a process starting at the hospital where people arrived in order to be diagnosed. Before any examination or testing, each person was asked to fill in the questionnaire containing questions relevant to COVID-19 diagnosis. Initially, the survey contained a few questions about the basic symptoms, consisting of the occurrence of temperatures exceeding 38 \({}^{\circ}\)C, cough, and dyspnoea. With time and increasing knowledge about the COVID-19 characteristics, the survey was enriched with further questions and options. When the final diagnosis resulting from the SARS-CoV-2 test, was known, the survey was anonymised, scanned, tagged with the SARS-CoV-2 test result, and sent to the database of survey images. Next, the information encapsulated in each survey was transformed into a feature vector, i.e., an example in our data set.  
The questionnaires were filled in by patients themselves. People waiting to be admitted to the hospital for further tests may feel unwell and anxious, which affects the consistency and quality of completed questionnaires. Therefore, a synthetic and unambiguous form of the survey was developed, which is now utilised within the web application presented in Section 8, which is one of the results of this research. Nevertheless, due to the manual nature of data collection, the data were subject to additional inspection to remove errors introduced while completing the survey.  
The collected data set consisted of 3114 patient records. Each patient was described by 32 attributes. Within these attributes, the following classes of patient characteristics can be identified:  
* 18 attributes describing symptoms;
* 7 attributes listing comorbidities;
* 3 attributes representing the patient's condition.  
The other attributes include epidemiological information, such as age, sex, blood group, and contact with infection. Each patient was classified by two conditions:  
* Symptoms: Healthy/Sick;
* SARS-CoV-2 test result: Positive/Negative.  
The quantitative characteristics of the collected sample from the population on the basis of the classification listed above are presented in Table 2.  
In the presented study, patients who experienced disease symptoms (Sick) were taken into consideration, i.e., 1941 people, as reported in Table 2. From this group, 577 patients, surveyed mainly in August and September, were extracted for final classification evaluation (test set). The characteristics of the test set taking into account SARS-CoV-2 diagnosis are presented in Table 3.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **SARS-CoV-2 (\(-\))** & **SARS-CoV-2 (\(+\))** & **Total** \\ \hline Healthy & 1000 & 173 & 1173 \\ Sick & 1355 & 586 & 1941 \\ Total & 2355 & 759 & 3114 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Quantitative characteristics of the main analysed data set.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **SARS-CoV-2 (\(-\))** & **SARS-CoV-2 (\(+\))** & **Total** \\ \hline Sick & 393 & 184 & 577 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Quantitative characteristics of the test data set.