## 7 Conclusions and Future Work  
The application has the potential to improve the efficiency and precision of the diagnosis of cardiovascular diseases, particularly in resource-limited settings where access to specialized medical personnel may be limited. By providing users with a tool to identify potential diagnoses and guide further testing, the application can help ensure that patients receive timely and appropriate care. Given that the application is based on novel research, accurate verification is needed.  
There are many directions in which this work could be extended in the future:  
1. One potential avenue for future work is to improve the symptom checker by adding more detailed and specialized questions and a description of the database to create a more comprehensive and accurate diagnostic tool.
2. The evaluation of the processing time and its influence on the accuracy.
3. Another potential direction is to expand the range of diseases covered by the application. Although the current version focuses on major cardiovascular diseases, there is the potential to add support for other types of disease or health conditions.  
Another area of future work is the integration of the application with electronic medical record systems, allowing for the seamless exchange of data and a more efficient diagnosis and treatment.  
Developing a mobile version of the application that allows users to access it from their smartphones or tablets.  
Adding a feature that allows users to track their symptoms over time could aid in the diagnosis and management of chronic diseases. Integrating the application with wearable devices, such as fitness trackers or smartwatches, allows continuous monitoring of vital signs and other health metrics.  
conceptualization, R.D., E.O.B. and S.S.; methodology, R.D. and E.O.B.; software, E.O.B. and R.D.; validation, R.D. and E.O.B.; formal analysis, R.D. and E.O.B., investigation, R.D., E.O.B., S.S. and M.T.I; resources, R.D.; data curation, E.O.B. and R.D.; writing--original draft preparation, R.D., E.O.B., N.P., S.S. and M.T.I; writing--review and editing, R.D., N.P., SS., M.T.I. and A.P.; visualization, E.O.B., R.D. and S.S.; supervision, R.D., E.T., M.G. and W.G.; project administration, R.D., E.T., M.G. and W.G; funding acquisition, R.D., E.T. and M.G. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding and The APC was funded by University of Lubeck.  
The study was conducted in accordance with the Declaration of Helsinki, and was approved by the Ethics Committee of Medical University of Silesia (resolution number KNW/0022/KB1/79/18 taken on 16 October 2018).  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
The data presented in this study are available upon request from the corresponding author. The data are not publicly available due to privacy.  
We thank [PERSON], [PERSON], and [PERSON] for providing useful insights regarding the design and application of the ontology and for helping revise the manuscript.  
The authors declare no conflicts of interest.  
The following abbreviations are used in this manuscript:  
A1 Artificial Intelligence  
CHD Coronary heart disease  
CHF Congenital heart failure  
CVA Cerebrovascular accident  
CVD Cardiovascular disease  
DM2 Diabetes mellitus 2  
ECG Electroccardiography, electrocardiogram  
FP False positive  
FN False negative  
FRS Framingham risk score  
GUI Graphical user interface  
HF Heart failure  
HPO Human phenotype ontology  
HTN Hypertension  
ISH International Society of Hypertension  
NCD Noncommunicable disease  
NPV Negative predictive value  
PPV Positive predictive value  
SCORE Systematic coronary risk evaluation  
SBP Systolic blood pressure  
SQL Structured query language  
TP True positive  
TN True negative