AI-Based Prediction of Myocardial Infarction Risk as an Element of Preventive Medicine

Abstract

The incidence of myocardial infarction (MI) is growing year on year around the world. It is considered increasingly necessary to detect the risks early, respond through preventive medicines and, only in the most severe cases, control the disease with more effective therapies. The aim of the project was to develop a relatively simple artificial-intelligence tool to assess the likelihood of a heart infarction for preventive medicine purposes. We used binary classification to determine from a wide variety of patient characteristics the likelihood of heart disease and, from a computational point of view, determine what the minimum set of characteristics permits. Factors with the highest positive influence were: cp, restecg and slope, whilst factors with the highest negative influence were sex, exang, oldpeak, ca, and thal. The novelty of the described system lies in the development of the AI for predictive analysis of cardiovascular function, and its future use in a specific patient is the beginning of a new phase in this field of research with a great opportunity to improve pre-clinical care and diagnosis, and accuracy of prediction in preventive medicine.

Artificial intelligence in the design and production of personalized 3D printed products – conclusions from the project “Things are for People”

“…Na Wydziale Informatyki opracowano system medycyny prewencyjnej (rys. 3) [11] oraz systemy do analizy ruchu [12][13][14], jakości życia [15] czy wypalenia zawodowego [16][17][18][19] oparte na AI.…”

Prediction of Coronary Artery Disease using Artificial Intelligence – A Systematic Literature Review

“…The SWOT analysis highlights the significance of any system's potential strengths. Throughout the deployment of an innovative digital healthcare system, weaknesses and threats should be addressed [100].…”

Machine Learning Classification for a Second Opinion System in the Selection of Assistive Technology in Post-Stroke Patients

“…This approach allows the integration of data from different sources to provide earlier and more accurate diagnosis and prognosis of a patient's condition and take appropriate preventive and therapeutic actions [30][31][32] (Figures 4 and 5). Preventive medicine is based onsystems already in place that could change the face of medicine in the future, focusing on the prevention of disease and secondary changes and maintaining the best possible health (including the functional state of the user) instead of responding to a decline in health (functional state) in the form of therapeutic interven-tion [33]. The use of artificial intelligence has already repeatedly proven its usefulness in large, complex systems, including monitoring and diagnostics [34][35][36].…”